JP2010039946A - Image processor, imaging device, image processing method and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image processor for generating a blur image free from discontinuous boundary or edge blur. <P>SOLUTION: The image processor extracts an object area from acquired image information (102 and 103), and then acquires a plurality of processing areas including the object area based on the size of the extracted object area (111). The processor performs different blur processing respectively to the acquired processing area to generate a blur image of the acquired image information (104 and 105). <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to an image processing apparatus, an imaging apparatus, an image processing method, and a program for performing blur processing on image information.

  Since an imaging device such as a digital camera generally has a small image sensor, the focal length of an imaging optical system necessary for taking an image is shortened. An imaging device such as a compact camera has a smaller lens size than an imaging device such as a single-lens reflex camera.

  Here, if the focal length is short and the lens size is small, the depth of field will be deep even if the F-number of the photographing optical system is the same. For this reason, when photographing with an imaging device such as a digital camera, the focus is on a relatively wide distance range as compared with an imaging device such as a single-lens reflex camera.

  As a result, an imaging apparatus such as a digital camera can obtain an image with less blur when an image having the same brightness as that of an imaging apparatus such as a single-lens reflex camera is captured. However, when shooting an image that requires background blur, such as a portrait, the background is also clearer. On the contrary, the expressive power of the image is lower than that of an imaging device such as a single-lens reflex camera. It will end up.

Here, in order to blur the background of image data captured by a camera having a deep depth of field, Patent Document 1 discloses an invention in which a blurring process is performed according to a shooting distance. Specifically, the image data is divided into a plurality of small blocks, and the shooting distance of each block is measured. Then, according to the measured shooting distance, blur processing is performed for each block, and a plurality of blocks subjected to the blur processing are synthesized. In the invention disclosed in this patent document 1, since the blurring process according to the shooting distance is performed for each block, the blurring process suitable for the background can be performed.
JP 2000-259823 A

  However, the invention disclosed in Patent Document 1 does not perform the blurring process on the main subject image, but performs the blurring process on the background image according to the shooting distance, and combines the two images to perform the blurring process suitable for the background. It is decided to generate image data that has been subjected to.

  For this reason, in the background blur processing method disclosed in Patent Document 1, when combining an object block not subjected to blur processing and an object block subjected to blur processing, as shown in FIG. A change in contrast occurs, resulting in a discontinuous boundary.

  In addition, when performing blurring processing on a portion that seems to be a background, an edge is widened because a low-pass filter is applied. The background is far, and the stronger the low-pass filter, the wider the edge. Therefore, as shown in FIG. 2, when the object is cut out and pasted to the background block, the object portion also spreads, and edge blurring occurs. In particular, when the color of the object is different from the color of the background, the color blur becomes conspicuous.

  The present invention has been made in view of the above circumstances, and provides an image processing device, an imaging device, an image processing method, and a program capable of generating a blurred image without discontinuous boundaries and edge blurring. For the purpose.

  In order to achieve this object, the present invention has the following features.

<Image processing device>
An image processing apparatus according to the present invention includes an extraction unit that extracts an object region from the acquired image information, and a region that acquires a plurality of processing regions including the object region based on the extracted size of the object region. The image processing apparatus includes: an acquisition unit; and a generation unit that performs different blurring processing on the acquired processing area and generates a blurred image of the acquired image information.

<Imaging device>
An imaging apparatus according to the present invention includes the above-described image processing apparatus.

<Image processing method>
According to the image processing method of the present invention, an extraction step for extracting an object region from the acquired image information and a plurality of processing regions including the object region are acquired based on the extracted size of the object region. And a generation step of generating a blurred image of the acquired image information by performing different blurring processes on the acquired processing area.

<Program>
A program according to the present invention causes a computer to execute the image processing method described above.

  According to the present invention, it is possible to generate a blurred image without discontinuous boundaries and blurring of edges.

  First, an outline of the image processing apparatus of the present embodiment will be described.

  The image processing apparatus according to the present embodiment performs low-pass filter processing on the original image step by step to create a plurality of image data shown in FIGS. FIG. 5 shows image data created by applying the strongest low-pass filter to the background portion. FIG. 4 shows image data created by applying a low-pass filter weaker than the low-pass filter of FIG. FIG. 3 shows image data created by applying a weaker low-pass filter than the low-pass filter of FIG.

  The image processing apparatus according to the present embodiment cuts out the region 3 in FIG. 5 and pastes it on the output image shown in FIG. Next, a circle portion indicating the region 2 in FIG. 4 is cut out and pasted on the output image shown in FIG. Next, a circle portion indicating the region 1 in FIG. 3 is cut out and pasted on the output image shown in FIG. As a result, it is possible to generate a blurred image with no discontinuous boundaries and no blurring of edges.

(First embodiment)
Hereinafter, the image processing apparatus of the present embodiment will be described in detail with reference to the accompanying drawings. In the following description, an image processing apparatus mounted on the imaging apparatus will be described as an example.

<Configuration of image processing apparatus>
First, the configuration of the image processing apparatus of this embodiment will be described with reference to FIG. FIG. 7 is a block diagram illustrating a configuration of an image processing apparatus mounted on the imaging apparatus.

  The image processing apparatus according to the present embodiment includes an image input unit 101, an image region dividing unit 102, an object extracting unit 103, an object edge processing unit 111, an image blur processing unit 104, an image composition unit 105, an image output unit 106, and camera parameter input. Unit 107, distance information acquisition unit 108, blur function acquisition unit 109, and blur function DB 110.

The image input unit 101 inputs an image to the image region dividing unit 102.
The image area dividing unit 102 finely divides an image.

  The object extraction unit 103 combines small areas finely divided by the image area division unit 102 and extracts meaningful objects. Here, the meaningful object means that the foreground and the background are distinguished. In the present embodiment, if the foreground and the background can be distinguished and the distance between the objects is known, the background blurring process can be realized. The distance between the objects is acquired from the distance information acquisition unit 108.

  The object edge processing unit 111 creates a mask (processing region) for designating an area that is slightly larger than the object region as shown in FIGS. 3 to 5 based on the object extracted by the object extracting unit 103.

  The image blur processing unit 104 performs blur processing on the object extracted by the object extraction unit 103 based on the blur function filter to create a plurality of blur images (backgrounds). The blur function filter is acquired from the blur function acquisition unit 109.

  The image compositing unit 105 uses the plurality of different size masks (processing areas) created by the object edge processing unit 111 and the plurality of blurred images (background) created by the image blur processing unit 104 to , And a blurred image (background).

  The image output unit 106 outputs the image synthesized by the image synthesis unit 105.

  The camera parameter input unit 107 inputs camera parameters.

  The distance information acquisition unit 108 acquires distance information. A detailed internal configuration of the distance information acquisition unit 109 is shown in FIG.

  The distance information acquisition unit 109 includes a reduced image input unit 201, an edge information calculation unit 202, a distance information calculation unit 203, a distance information output unit 204, and a lens focus adjustment unit 205.

The lens focus adjustment unit 205 adjusts the focus of the camera lens.
The reduced image input unit 201 inputs images at a plurality of different focal positions to the edge information calculation unit 202.

The edge information calculation unit 202 divides the image into a plurality of image blocks based on a plurality of images at different focal positions input from the reduced image input unit 201, and calculates a total value of contrast values in the block area at the same position. It is.
The distance information calculation unit 203 compares the contrast values in the block areas at the same position, and calculates the shooting distance.
The distance information output unit 204 outputs the distance information acquired by the distance information calculation unit 203 to the object extraction unit 103 and the blur function acquisition unit 109.

  The blur function DB 110 stores a blur function filter. The data structure of the blur function DB 110 is shown in FIG.

  As shown in FIG. 9, the blur function DB 110 stores a distance difference, a focal length, an F value, an aperture shape, and a blur function filter in association with each other. For this reason, the content of the filter f of the blur function changes according to the difference in distance, the focal length, the F value, and the shape of the aperture. The blur function filter f is an N × N filter. The value of each element varies depending on camera parameters and shooting distance. Based on the design value of the camera lens, the value of each element is calculated in advance and stored in the blur function DB 110.

  The blur function acquisition unit 109 acquires a blur function filter f from the blur function DB 110 based on the camera parameters input from the camera parameter input unit 107.

  In the image processing apparatus of the present embodiment, the image area dividing unit 102 and the object extracting unit 103 realize an extracting unit that extracts an object area from image information.

  Further, the object edge processing unit 111 realizes area acquisition means for acquiring a plurality of processing areas including the object area based on the size of the object area extracted by the extraction means.

  In addition, the image blur processing unit 104 and the image synthesis unit 105 perform different blur processing on the processing region acquired by the region acquisition unit, and realize a generation unit that generates a blurred image of the acquired image information.

<Processing operation of image processing apparatus>
Next, the processing operation of the image processing apparatus according to the present embodiment will be described with reference to FIGS. 7, 8, and 10. FIG. 10 is a diagram illustrating a processing operation of the image processing apparatus according to the present embodiment.

<Processing of steps A1 to A3>
First, the processing operation of the distance information acquisition unit 108 shown in FIG. 7 will be described with reference to FIGS. 7, 8, and 10.

  In the distance information acquisition unit 108 of the present embodiment, the lens focus adjustment unit 205 adjusts the focus of the camera lens, and the reduced image input unit 201 inputs images of a plurality of different focal positions to the edge information calculation unit 202 ( Step A1).

  The edge information calculation unit 202 divides into a plurality of image blocks based on a plurality of images at different focal positions input from the reduced image input unit 201, and obtains a total value of contrast values in a block region at the same position ( Step A2).

  The distance information calculation unit 203 compares the contrast values in the block areas at the same position, and calculates the shooting distance. For example, it is determined that the image with the highest contrast value is in focus on the block, and the shooting distance is calculated based on the focal position of the image frame. The distance information calculation unit 203 calculates shooting distance information for all blocks, and acquires distance information for each block (step A3). The distance information calculation unit 203 can also acquire distance information using a distance measurement sensor. The distance information output unit 204 outputs the distance information acquired by the distance information calculation unit 203 to the object extraction unit 103 and the blur function acquisition unit 109.

<Processing operations of steps B1 and B2>
Next, processing operations of the camera parameter input unit 107 and the blur function acquisition unit 109 shown in FIG. 7 will be described with reference to FIGS.

  First, the camera parameter input unit 107 inputs camera parameters to the blur function acquisition unit 109 (step B1).

  The blur function acquisition unit 109 acquires a blur function filter from the blur function DB 110 based on the camera parameters input from the camera parameter input unit 107 (step B2). The blur function acquisition unit 109 outputs the blur function filter acquired from the blur function DB 110 to the image blur processing unit 104.

<Processing of steps S1 to S8>
Next, referring to FIGS. 7 and 10, the image input unit 101, the image region dividing unit 102, the object extracting unit 103, the object edge processing unit 111, the image blur processing unit 104, the image composition unit 105, The processing operation of the image output unit 106 will be described.

  First, the image input unit 101 inputs an image to the image region dividing unit 102 (step S1).

  The image area dividing unit 102 finely divides the image input from the image input unit 101 (step S2). The image region dividing unit 102 divides the image using information such as the edge and color of the image. In the area division of an image, areas of almost the same color are extracted as one lump as shown in FIG. In FIG. 11, a block object A, an object B, and a background C of the same color are extracted.

  Based on the color of each pixel of the image, the image region dividing unit 102 calculates a color difference with the color of the adjacent pixel, and if the color difference is equal to or less than a predetermined threshold, determines that the same chunk is Extract as a region. The image area dividing unit 102 extracts a block having substantially the same contrast as one area.

  Here, with reference to FIG. 12, the processing operation of area division in step S2 will be described in detail.

  First, the image is color space converted, the RGB image is converted to YUV, and a YUV image is generated (step S21). Y is the luminance of the image, and U and V indicate the color characteristics of the pixel. U is the difference between the luminance signal and the B signal, and V is the difference between the luminance signal and the R signal.

  Next, a filtering process is performed on each of the Y, U, and V components (step S22). By filtering, it is possible to average noise components and small regions that change rapidly, and to easily create a lump with the same characteristics. Note that the filter used for the filtering process is not particularly limited as long as noise removal and a smoothing effect can be obtained, and any filter can be applied. For example, Gaussian with a smoothing effect can be applied.

  Next, region generation is performed based on the Y, U, and V components subjected to the filtering process (step S23). The filtered Y, U, and V components are determined as the same lump if the difference between adjacent pixels is smaller than a predetermined threshold, and a lump is formed. The threshold is set for each of Y, U, and V. The threshold values are adjusted and set in advance through experiments, and the respective threshold values are stored in a memory. Thereby, it is possible to generate a small region with a small characteristic difference. It should be noted that the region division may be performed using the U and V threshold values, and the region division may be performed using the respective threshold values including the luminance value Y threshold value. By the processing in step S22, it is possible to separate into the same color block object A, object B, and background C as shown in FIG.

  Next, the small area is deleted (step S24). A small region may be generated due to the influence of noise or isolated points. For this reason, a threshold value for the area is provided, and an area smaller than the threshold value is merged with the adjacent area. However, in the case of merging, it is combined with an area having the smallest luminance and color difference with the adjacent area. The threshold of the minimum area can be adjusted arbitrarily and is set in advance.

  Next, the region merged in step S24 is output as a region division result (step S25). The fused region becomes a fused region with a close color or a fused region with little contrast change. As a result, as shown in FIG. 11, a lump having the same color and little change in contrast is extracted as one region and separated into an object A, an object B, and a background C. Thereby, the image region dividing unit 102 can finely divide the image input from the image input unit 101 and divide the image into small regions.

  Next, the object extraction unit 103 combines the small areas divided by the image area division unit 102 in step S2, and extracts meaningful objects (step S3).

  Since the image area dividing unit 102 created the object chunks A, B, and C in step S2, the object extracting unit 103, based on the distance information, if the distance difference between the objects A and B and the background C is known, Background blur processing can be realized. For this reason, as shown in FIG. 13, if there is a block with a high certainty factor in each of the areas A, B, and C, it is possible to acquire distance information between objects using the block.

  However, it is possible to perform background blurring processing even if there is a portion from which distance information cannot be acquired. For example, when distance information can be acquired by one block in each object, the distance information is used as the distance information of the object. For this reason, it is not necessary to acquire distance information of other blocks.

  In the present embodiment, the object extraction unit 103 uses a person's head and body as small areas, and divides the figure into two areas. And since the distance of the block in a head area | region and the block in a body area | region is substantially the same, a head and a body are combined and it extracts as one object. In addition, the blocks in the head region and the blocks in the body region are extracted as different objects because the blocks are different in distance from the blocks in the adjacent wood region. As a result, as shown in FIG. 13, it is possible to separate the object A, the object B, and the background C from each other.

  Next, based on the object extracted by the object extraction unit 103 in step S3, the object edge processing unit 111 sets a mask (processing region) for designating a region that is slightly larger than the object region as shown in FIGS. Create (step S4). As a result, the object edge processing unit 111 creates a plurality of masks (processing regions) having different sizes for making the edge portions continuous.

  The area that is slightly larger is an area that is N pixels away from the outer periphery of the object extracted by the object extraction unit 103 in step S3 (see FIGS. 3 to 6). Here, N is variable. However, if the object extraction accuracy is high, the mask step close to the object is reduced, and the size of the pixel N is gradually increased from the object to the background. If the object extraction accuracy is low, the mask steps from the object to the background are made equal, or the closer to the object, the larger the N pixel mask step interval. As a result, the object extraction error can be made inconspicuous.

  When creating a plurality of masks (processing areas) having different sizes, it is preferable to change the number of masks to be created according to the distance between objects and the difference in blurring between objects. For example, if the difference in distance between objects is large, the number of masks is increased stepwise to blur continuously. For this reason, it is preferable that the distance between objects and the number of masks are associated with each other and recorded in advance in a memory, and the number of masks corresponding to the measured distance between objects is called from the memory.

  Next, the image blur processing unit 104 acquires a blur function filter from the blur function acquisition unit 109, and performs blur processing on the object based on the acquired blur function filter (step S5). When performing the blurring process, the blurring process is performed on the object based on a plurality of blur function filters to generate a plurality of blurred images as shown in FIGS. 3 to 5 (step S6). As a result, the image blur processing unit 104 generates a plurality of blur images.

Here, a method for determining the degree of blurring in the object surrounding area will be described.
The image blur processing unit 104 adjusts the blur condition by the strength of the blur function filter. The closer to the object, the weaker the blur function filter. Then, the closer the object is to the farther away, the stronger the blur function filter. In this embodiment, the blur function is adjusted based on the blur function filter acquired from the blur function DB 110 by the blur function acquisition unit 109. It is also possible to change the strength of the mask depending on the distance between the objects. In this case, the greater the distance between the objects, the stronger the mask blur.

  Next, the image composition unit 105 generates an object and a plurality of images based on the plurality of masks (processing regions) having different sizes generated in step S4 and the plurality of blurred images (background) generated in step S6. The blurred image (background) is synthesized (step S7). When combining an object and multiple blurred images (background), use multiple different size masks (processing areas) to cut out the images from multiple blurred images (background) and combine the images. Then, the image shown in FIG. 6 is generated. Specifically, the region 3 in FIG. 5 is cut out and pasted on the output image shown in FIG. Next, a circle portion indicating the region 2 in FIG. 4 is cut out and pasted on the output image shown in FIG. Next, a circle portion indicating the region 1 in FIG. 3 is cut out and pasted on the output image shown in FIG. As a result, it is possible to generate a blurred image with no discontinuous boundaries and no blurring of edges.

  Next, the image output unit 106 outputs the image synthesized in step S7 (step S8).

<Operation / Effect of Image Processing Apparatus of Present Embodiment>
As described above, the image processing apparatus according to the present embodiment performs low-pass filter processing on the original image step by step to create a plurality of image data shown in FIGS. 5 is cut out and pasted on the output image shown in FIG. Next, a circle portion indicating the region 2 in FIG. 4 is cut out and pasted on the output image shown in FIG. Next, a circle portion indicating the region 1 in FIG. 3 is cut out and pasted on the output image shown in FIG. As a result, the image processing apparatus according to the present embodiment can generate a blurred image without discontinuous boundaries and without edge blurring.

<Imaging Device Incorporating Image Processing Device of Present Embodiment>
Next, the hardware configuration of the imaging apparatus equipped with the above-described image processing apparatus shown in FIG. 7 will be described with reference to FIG. FIG. 14 is a block diagram illustrating a hardware configuration of the imaging apparatus according to the present embodiment.

  The imaging apparatus of the present embodiment includes an imaging optical system 1, a mechanical shutter 2, a CCD (Charge Coupled Device) 3, a CDS (Correlated Double Sampling) circuit 4, an A / D converter 5, a motor driver 6, a timing signal generator 7, Image processing circuit 8, CPU 9, RAM (Random Access Memory) 10, ROM (Read Only Memory) 11, SDRAM (Synchronous DRAM) 12, compression / decompression circuit 13, memory card 14, operation unit 15, LCD16 Yes.

  Subject light is incident on the CCD 3 through the photographing optical system 1. Further, a mechanical shutter 2 is disposed between the photographing optical system 1 and the CCD 3, and incident light on the CCD 3 can be blocked by the mechanical shutter 2. The photographing optical system 1 and the mechanical shutter 2 are driven by a motor driver 6.

  The CCD 3 converts the optical image formed on the imaging surface into an electrical signal and outputs it to the CDS circuit 4 as analog image data. The CDS circuit 4 removes the noise component of the image information output from the CCD 3 and outputs it to the A / D converter 5. The A / D converter 5 converts it into a digital value and outputs it to the image processing circuit 8.

  The image processing circuit 8 uses the SDRAM 12 to perform various image processing such as YCrCb conversion processing, white balance processing, contrast correction processing, edge enhancement processing, and color conversion processing.

  The white balance process is a process for adjusting the color density of image information. The contrast correction process is a process for adjusting the contrast of the image information. The edge enhancement process is a process for adjusting the sharpness of image information. The color conversion process is a process for adjusting the hue of image information.

  Further, the image processing circuit 8 displays on the LCD 16 image information that has undergone signal processing and image processing. Further, the image processing circuit 8 records the image information subjected to the signal processing and the image processing on the memory card 14 via the compression / decompression circuit 13.

  The compression / decompression circuit 13 compresses the image information output from the image processing circuit 8 according to an instruction from the operation unit 15, outputs the compressed image information to the memory card 14, and decompresses the image information read from the memory card 14 to perform image processing. Output to circuit 8.

  The CPU 9 controls the timing of the CCD 3, the CDS circuit 4, and the A / D converter 5 through a timing signal generator 7 that generates a timing signal. Further, the CPU 9 controls the image processing circuit 8, the compression / decompression circuit 13, and the memory card 14.

<Processing Operation of Imaging Device of Present Embodiment>
Next, the processing operation of the imaging apparatus according to the present embodiment will be described with reference to FIGS. 10 and 14.
The imaging apparatus of the present embodiment measures subject distance information. Next, while moving the motor driver 6, the photographing optical system 1 and the mechanical shutter 2 are controlled, the focal position is changed, and a plurality of reduced images are input to the SDRAM 12. As a result, a plurality of reduced images having different shooting distances are input to the SDRAM 12 (step S1).

  Next, actual shooting is performed, and a large-size image for background blur processing is input to the SDRAM 12 (step A1). Next, the distance measurement program is called from the ROM 11, and the processes of steps A2 to A3 shown in FIG. 10 are performed. Specifically, each image is divided into blocks, and the sum of contrast values in the same position block is calculated. The block with the highest contrast value is determined to be in focus at this position, and this is set as the image forming position of the frame. Then, the subject distance is calculated based on the imaging position. Thereby, distance information can be extracted.

  Next, the area division / object extraction program is called from the ROM 11, and the processes of steps S2 to S3 shown in FIG. 10 are performed. Specifically, the image edge information and color information are used to divide the image into smaller areas. Next, the small areas are put together and objects are extracted as shown in FIG. When extracting objects, small areas having common attributes are grouped based on color characteristics and edge characteristics. Further, the measured distance information is also used when collecting the areas. Small areas that are close to each other are grouped together as object candidates. An object is a meaningful area such as a person, foreground, or background. The shooting distance in each area is different. As a result, the image can be divided into blocks as shown in FIG. Within each block, the distance is measured by distance measurement software. Further, the distances A, B, and C shown in FIG. 13 are acquired from the block.

  Next, the process of step B2 shown in FIG. 10 is performed to obtain a blur function filter of the objects A, B, and C. When the object A is determined as the main subject, the blurring process is not performed on A. Based on the shooting distance and camera parameters of the object B and the background C, the blur function filter is acquired from the blur function DB 110. The blur function filter is f shown in FIG. 9, and a blur function filter corresponding to the camera parameter and the shooting distance is acquired from the blur function DB 110.

  Next, the processing of steps S5 to S6 shown in FIG. 10 is performed, the captured original image A is filtered by the filter f # B, and the filtered image B is stored in the SDRAM 12. Next, filtering processing is performed on the original image A with the filter f_C, and the image C on which filtering processing has been performed is also stored in the SDRAM 12.

  Since the distance between the object B and the object C is different, a strong low-pass filter is applied to a distant object to blur it strongly. As a result, the same camera blur as the input camera parameter can be realized. For example, when a single-lens reflex parameter is input, an image with the same background blur as that single-lens reflex camera can be created.

  Further, the process of step S4 shown in FIG. 10 is performed to generate a mask for edge processing.

  Next, the process of step S7 shown in FIG. 10 is performed, the part of the object A is cut out from the original image A, the object B is cut out from the image B, the background part C is cut out from the image C, and the image is synthesized. In this case, a plurality of filtering processes are performed in accordance with a mask having a size slightly different from that of the object, and a plurality of blurred images are stored in the SDRAM 12. As for the strength of the filter, the distance between the object and the background is divided stepwise, and the blur function filter is acquired from the blur function DB 110 based on the distance. An image is cut out from a plurality of masks and a plurality of blurred images to generate a background blurred image.

  The imaging apparatus according to the present embodiment has a module configuration including the background blur function described above, and the CPU (processor) 9 reads a program from the ROM 11 and executes it.

(Second Embodiment)
Next, a second embodiment will be described.

  The image processing apparatus according to the first embodiment changes the blur function filter in accordance with the distance between objects, and adjusts the degree of blurring in the object surrounding area.

  The image processing apparatus according to the second embodiment sets a plurality of areas between objects, changes the blur function filter based on the difference between the distances between the objects and the imaging distance, and determines the degree of blurring in each of the set areas. It is characterized by adjusting. Thereby, it is possible to set a plurality of areas between objects and create a blurred image of each set area.

  If the distance between the object A and the object B is known, it is possible to adjust the blur function filter. Also, if you know the shooting distance of objects and the distance between objects, set multiple areas between objects, change the blur function filter based on the difference between the distance between objects and shooting distance, and set the above It is possible to adjust the degree of blurring in each area. In this case, a blur function filter is calculated based on the shooting distance and the difference between the shooting distances, and the calculated blur function filter is stored in the blur function DB 110 in association with the difference between the shooting distance and the shooting distance. Based on the actually obtained shooting distance and the difference between the shooting distances, a blur function filter corresponding to the difference between the shooting distance and the shooting distance is obtained from the blur function DB 110, and the obtained blur function filter is used. Adjust the degree of blur in each area to create a blurred image. Thereby, it is possible to set a plurality of areas between objects and create a blurred image of each set area.

(Third embodiment)
Next, a third embodiment will be described.

  In the first and second embodiments, the image processing apparatus mounted on the imaging apparatus illustrated in FIG. 14 has been described as an example. For this reason, as shown in FIG. 10, the image input in step S1 and the different focus image input in step A1 are performed separately.

  The third embodiment is characterized in that an image file is input, the image input in step S1 shown in FIG. 10 and the different focus image input in step A1 are performed together, and distance information is extracted from the image file. To do. As a result, the same processing as that of the image processing apparatus mounted on the imaging apparatus described above can be performed by a general image processing apparatus. The image processing apparatus according to the present embodiment will be described below with reference to the accompanying drawings.

<Hardware Configuration of Image Processing Apparatus of Present Embodiment>
First, the hardware configuration of the image processing apparatus of this embodiment will be described with reference to FIG. FIG. 15 is a block diagram illustrating a hardware configuration example of the image processing apparatus according to the present embodiment.

  The image processing apparatus according to the present embodiment includes a CPU 24, a RAM 21, a ROM 22, an I / F 23, an HDD 25, a CD-ROM driver 20, and a memory card driver 27.

  The CPU 24 centrally controls each part. The ROM 22 is a read-only memory that stores a BIOS and the like. The RAM 21 stores various data in a rewritable manner and functions as a work area for the CPU 24. The HDD 25 stores a control program and the like. The CD-ROM driver 20 reads a CD (Compact Disc) -ROM 28. The memory card driver 27 reads the memory card 29. The I / F 23 is an interface that manages communication with the printer unit and the like.

  The CD-ROM 28 stores a predetermined control program. The CPU 24 reads the control program stored in the CD-ROM 28 with the CD-ROM drive 26 and installs it in the HDD 25. As a result, various processes similar to those in the above-described embodiment can be performed. The memory card 29 stores image information and the like and is read by the memory card driver 27.

  As the storage medium, not only the CD-ROM 28 and the memory card 29 but also various types of media such as various optical disks such as DVD, various magnetic disks such as various magneto-optical disks and floppy (registered trademark) disks, and semiconductor memory are used. It is also possible.

  It is also possible to download a program from a network such as the Internet and install it on the HDD 25. In this case, the storage device that stores the program on the server on the transmission side also corresponds to the storage medium of the present embodiment. Note that the program can also run on a predetermined OS (Operating System). In that case, it is also possible to let the OS take over some of the various processes described below. It can also be included as part of a group of program files that constitute predetermined application software such as word processing software or an OS.

  It is also possible to store a program executed by the image processing apparatus of the present embodiment on a computer connected to a network such as the Internet and download it via the network. It is also possible to provide or distribute a program executed by the image processing apparatus of the present embodiment via a network such as the Internet. It is also possible to provide the program of the present embodiment by incorporating it in a ROM or the like in advance.

<Processing Operation of Image Processing Apparatus of Present Embodiment>
Next, processing operations performed by the image processing apparatus according to the present embodiment will be described with reference to FIG.

  As shown in FIG. 16, the processing operation performed by the image processing apparatus of the present embodiment inputs an image file (step S′1), extracts distance information from the image file, and extracts the extracted distance information as an object. Output to the unit 103 and the blur function acquisition unit 109 (step A′3). The other processing operations are almost the same as those in FIG.

  As described above, the image processing apparatus of the present embodiment inputs an image file, and performs the image input in step S1 shown in FIG. 10 and the different focus image input in step A1 together (step S′1). Distance information is extracted from the image file (step A'3). As a result, the same processing as that of the image processing apparatus mounted on the imaging apparatus described above can be performed by a general image processing apparatus.

  The above-described embodiment is a preferred embodiment of the present invention, and the scope of the present invention is not limited to the above-described embodiment alone, and various modifications are made without departing from the gist of the present invention. Implementation is possible.

It is a figure which shows the state in which the sudden change of contrast generate | occur | produced. It is a figure which shows the state which the blur of edge generate | occur | produced. It is a figure which shows the image data produced by performing a low-pass filter process, and is a figure which shows the image data produced by applying a low-pass filter weaker than the low-pass filter of FIG. It is a figure which shows the image data produced by performing a low-pass filter process, and is a figure which shows the image data produced by applying a low-pass filter weaker than the low-pass filter of FIG. It is a figure which shows the image data produced by performing a low-pass filter process, and is a figure which shows the image data produced by applying the strongest low-pass filter to a background part. It is a figure which shows the output image data produced based on the image data shown in FIGS. It is a figure which shows the structure of the image processing apparatus of this embodiment. It is a figure which shows the detailed internal structural example of the distance information acquisition part 109 shown in FIG. It is a figure which shows the example of a data structure of the blurring function DB110. It is a figure which shows the processing operation of the image processing apparatus of this embodiment. It is a figure which shows the state which performed the area | region division of the image. FIG. 11 is a diagram showing an example of detailed processing operation of area division in step S2 shown in FIG. 10. It is a figure which shows the state which divided | segmented the image into the block. It is a figure which shows the hardware structural example of an imaging device. It is a figure which shows the hardware structural example of an image processing apparatus. It is a figure which shows the processing operation of the image processing apparatus of this embodiment.

Explanation of symbols

1 Shooting optical system 2 Mechanical shutter 3 CCD
4 CDS circuit 5 A / D converter 6 Motor driver 7 Timing signal generator 8 Image processing circuit 9 CPU
10 RAM
11 ROM
12 SDRAM
13 Compression / Expansion Circuit 14 Memory Card 15 Operation Unit 16 LCD
21 RAM
22 ROM
23 I / F
24 CPU
25 HDD
26 CD-ROM driver 27 Memory card driver 28 CD-ROM
DESCRIPTION OF SYMBOLS 29 Memory card 101 Image input part 102 Image area division part 103 Object extraction part 104 Image blurring process part 105 Image composition part 106 Image output part 107 Camera parameter input part 108 Distance information acquisition part 109 Blur function acquisition part 110 Blur function DB
111 Object Edge Processing Unit 201 Reduced Image Input Unit 202 Edge Information Calculation Unit 203 Distance Information Calculation Unit 204 Distance Information Output Unit 205 Lens Focus Adjustment Unit

Claims (8)

Extracting means for extracting an object region from the acquired image information;
An area acquisition means for acquiring a plurality of processing areas including the object area based on the extracted size of the object area;
Generating means for performing different blurring processing on the acquired processing area and generating a blurred image of the acquired image information;
An image processing apparatus comprising:   The image processing apparatus according to claim 1, wherein the area acquisition unit sequentially enlarges the extracted object area by a predetermined size to acquire a plurality of processing areas.   The image processing apparatus according to claim 1, wherein the generation unit performs different blurring processing on the processing region according to a distance from the object region.   An imaging apparatus comprising the image processing apparatus according to any one of claims 1 to 3. An extraction step of extracting an object region from the acquired image information;
An area acquisition step of acquiring a plurality of processing areas including the object area based on the extracted size of the object area;
A generation step of performing different blurring processing on the acquired processing area and generating a blurred image of the acquired image information;
An image processing method comprising:   6. The image processing method according to claim 5, wherein the area acquiring step sequentially expands the extracted object area by a predetermined size to acquire a plurality of processing areas.   The image processing method according to claim 5, wherein the generation step performs different blurring processing on the processing region according to a distance from the object region.   A program that causes a computer to execute the image processing method according to any one of claims 5 to 7.

Images