CN112564713B - High-efficiency low-time delay kinescope signal coder-decoder and coding-decoding method - Google Patents

High-efficiency low-time delay kinescope signal coder-decoder and coding-decoding method Download PDF

Info

Publication number
CN112564713B
CN112564713B CN202011368867.4A CN202011368867A CN112564713B CN 112564713 B CN112564713 B CN 112564713B CN 202011368867 A CN202011368867 A CN 202011368867A CN 112564713 B CN112564713 B CN 112564713B
Authority
CN
China
Prior art keywords
value
signal
run
coefficient
inverse
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202011368867.4A
Other languages
Chinese (zh)
Other versions
CN112564713A (en
Inventor
赵铁松
曾超洋
乔杨珺
房颖
徐艺文
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Fuzhou University
Original Assignee
Fuzhou University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Fuzhou University filed Critical Fuzhou University
Priority to CN202011368867.4A priority Critical patent/CN112564713B/en
Publication of CN112564713A publication Critical patent/CN112564713A/en
Application granted granted Critical
Publication of CN112564713B publication Critical patent/CN112564713B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • HELECTRICITY
    • H03ELECTRONIC CIRCUITRY
    • H03MCODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M13/00Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes
    • H03M13/65Purpose and implementation aspects
    • H03M13/6502Reduction of hardware complexity or efficient processing

Landscapes

  • Physics & Mathematics (AREA)
  • Probability & Statistics with Applications (AREA)
  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Compression, Expansion, Code Conversion, And Decoders (AREA)

Abstract

The invention provides a kinescope signal coder-decoder with high efficiency and low time delay and a coding-decoding method, wherein the coder consists of a signal amplifier, a discrete cosine transform module, a quantizer, a run-length coding module and an entropy coder; the decoder consists of an entropy decoder, a run-length decoding module, an inverse quantizer, an inverse discrete cosine transform module and an inverse amplifier. Compared with the existing advanced touch coding method, the high-efficiency low-time-delay kinesthesia signal codec design provided by the method has the advantages that the compression rate is reduced by 50% on average compared with a dead zone-based touch coding standard algorithm, and meanwhile, the distortion degree and the time delay are smaller.

Description

High-efficiency low-time delay kinescope signal coder-decoder and coding-decoding method
Technical Field
The invention belongs to the technical field of touch signal coding, and particularly relates to a high-efficiency low-time-delay kinescope signal coder-decoder and a coding-decoding method.
Background
The audio and video are common multimedia interaction content and act on various physiological senses of human beings. The scope of multimedia is not limited to audio and visual. Most users prefer multimedia interactive contents in which audio, video and touch are fused. Because of the stimulus of more sensory dimensions, such as the touch, an immersive experience can be constructed. Furthermore, studies have shown that there is a correlation between vision and touch, and that the touch pattern has an impact on both audible and visual media perception.
With the development of multimedia services, haptic signals are becoming one of the non-negligible carriers for multimedia. Kinesthesis (Kinesthetic) is one of two major components of haptic signals. The position, velocity, angular velocity, force and torque all fall within the category of kinesthetic signals. Such information can help the user determine the viscosity, hardness and inertia of the object by acting on the tactile senses of humans.
The current kinesthesia signal has the statistical characteristics of high sampling frequency and more degrees of freedom. High sampling rate is a necessary condition to ensure the performance and stability of the control loop of the haptic device and is also an objective need to significantly enhance the realism of the haptic system. The sampling rate of kinesthetic signals is typically higher than 1000Hz. Touch sensing devices are currently common in three degrees of freedom. With the rapid development of multimedia technology, haptic devices are easily developed with more degrees of freedom and transmit larger amounts of data. In order to facilitate the data transmission of the touch signal and avoid network congestion, the touch coding technology is very important. Current studies of haptic perception signals have not reached the same high quality level of vision and hearing. In particular, the problem of coding and decoding of haptic signals has yet to be further studied.
Disclosure of Invention
In order to fill the blank of the prior art, different influencing factors need to be considered in the establishment of the touch coding method, the invention creatively provides a high-efficiency, low-time-delay and perceptually lossless touch coding method. The high efficiency ensures better rate-distortion R-D performance, with the corresponding index amounts being the compression rate, i.e. "number of haptic bits after encoding" divided by "number of haptic bits before encoding", and the signal-to-noise ratio SNR. The low latency guarantees a lower coding latency, and the corresponding index amounts are the buffering latency and the computation latency. Perceptual lossless means that lossy is allowed, but not perceived by the user, the corresponding index amount is the haptic structure similarity HSSIM.
The invention adopts the following technical scheme:
a high efficiency low latency kinesthetic signal codec, characterized by: the encoder consists of a signal amplifier, a discrete cosine transform module, a quantizer, a run-length encoding module and an entropy encoder; the decoder consists of an entropy decoder, a run-length decoding module, an inverse quantizer, an inverse discrete cosine transform module and an inverse amplifier.
Preferably, the formula of the signal amplifier is as follows:
S' ori (i)=S ori (i)M,
wherein S is ori Representing the input of the signal amplifier, S' ori Representing the output of the signal amplifier, M representing the amplification factor of the signal;
the discrete cosine transform module adopts a 1-dimensional discrete cosine transform algorithm to transform signals from a time domain to a frequency domain to obtain a direct current coefficient and an alternating current coefficient; the current direct current coefficient is obtained by predicting the direct current coefficient of the previous coding sequence, the difference value of the current direct current coefficient and the direct current coefficient is used for carrying out quantization operation, and the current value of the alternating current coefficient is directly taken for carrying out quantization operation;
the formula of the quantizer is as follows:
quantization value = DCT coefficient/Q;
wherein Q is a quantization parameter;
the run length encoding module performs run length encoding on the quantized alternating current coefficient AC, and is expressed as follows: AC (Run, bits, value), where Run represents the number of zero-Value AC coefficients between two nearest non-zero-Value AC coefficients, i.e., run length, bits represents the number of Bits needed to store Value; value represents the magnitude Value of the current non-zero Value AC coefficient or the magnitude Value of the DC coefficient;
the output DC coefficient DC is: DC (Bits, value);
the entropy coder adopts arithmetic coding, wherein Run and Bits adopt 4-bit fixed length to carry out arithmetic coding, and Value adopts variable-length arithmetic coding;
the entropy decoder adopts an inverse algorithm of arithmetic coding, wherein Run and Bits execute the inverse algorithm of arithmetic coding by using a fixed length of 4 Bits, and Value adopts the inverse algorithm of variable-length arithmetic coding;
the run decoding module restores the intermediate state (Bits, value) to Value and executes an inverse algorithm for run coding;
the formula of the inverse quantizer is as follows:
DCT coefficient = quantization value x Q;
the inverse discrete cosine transform module adopts a 1-dimensional discrete cosine inverse transform algorithm;
the formula of the inverting amplifier is as follows:
wherein S' rec Representing the input of an inverting amplifier S rec Representing the output of the inverting amplifier.
Preferably, the sampling frequency of the encoder to the kinesthesia signal is 1000HZ, 8 sampling points are taken from each group of coding sequences, and 6 bit decimal values are reserved for each sampling point; the kinesthetic signal is a position signal or a force signal.
Preferably, in the signal amplifier, the position signal amplification Mp has a value of 200, and the force signal amplification Mf has a value of 50;
in the discrete cosine transform module, the number of time domain sampling points of a 1-dimensional discrete cosine transform algorithm is N=8, the obtained first DCT coefficient is a direct current coefficient, and the last seven DCT coefficients are alternating current coefficients;
the quantization parameter q= (4,4,16,32,48,64,80,96).
Preferably, the encoding parameters are determined by kinesthetic signal characteristics and the encoding delay is determined by a user perception threshold.
And a kinesthetic signal coding and decoding method with high efficiency and low time delay is characterized in that: comprises an encoding process and a decoding process;
the encoding process comprises the steps of:
step A1: sampling the kinesthesia signal, and amplifying the sampled signal by a signal amplifier;
step A2: transforming the signal from time domain to frequency domain by adopting a 1-dimensional discrete cosine transform algorithm to obtain a direct current coefficient and an alternating current coefficient;
step A3: carrying out quantization treatment on the output value after the transformation in the step A2;
step A4: run-length encoding is performed on the quantized alternating current coefficient AC, expressed as: AC (Run, bits, value), where Run represents the number of zero-Value AC coefficients between two nearest non-zero-Value AC coefficients, i.e., run length, bits represents the number of Bits needed to store Value; value represents the magnitude Value of the current non-zero Value AC coefficient or the magnitude Value of the DC coefficient;
the output DC coefficient DC is: DC (Bits, value);
step A5: an entropy coder is adopted for arithmetic coding, wherein Run and Bits adopt 4-bit fixed length for arithmetic coding, and Value adopts variable length arithmetic coding;
the decoding process comprises the steps of:
step B1: entropy decoding is carried out on the information obtained by encoding by adopting an inverse algorithm of arithmetic encoding;
step B2: restoring the intermediate state (Bits, value) to Value, and executing an inverse algorithm for run-length coding;
step B3: inverse quantization is carried out on the signals by adopting an inverse quantizer;
step B4: transforming the signal from the frequency domain to the time domain by adopting a 1-dimensional discrete cosine inverse transformation algorithm;
step B5: the signal is reconstructed using an inverse amplifier.
Preferably, the sampling frequency of the kinesthesia signal is 1000HZ, 8 sampling points are taken from each group of coding sequences, and each sampling point is reserved with 6 decimal places; the kinesthesia signal is a position signal or a force signal; in the signal amplifier, the value of the position signal amplification factor Mp is 200, and the value of the force signal amplification factor Mf is 50; in the discrete cosine transform module, the number of time domain sampling points of a 1-dimensional discrete cosine transform algorithm is N=8, the obtained first DCT coefficient is a direct current coefficient, and the last seven DCT coefficients are alternating current coefficients; in the quantization process and the inverse quantization process, the quantization parameter q= (4,4,16,32,48,64,80,96).
Compared with the prior art, the invention and the preferable scheme thereof have the following beneficial effects:
1. the invention provides an end-to-end touch coding method for the first time. The statistical characteristics of the haptic signal provide a theoretical basis for the proposed codec. Based on these characteristics, the end-to-end touch coding method is redesigned and optimized.
2. The invention realizes the high efficiency, low delay and perception lossless of the touch coding for the first time. The high efficiency ensures better rate-distortion R-D performance, with the corresponding index amounts being the compression rate, i.e. "number of haptic bits after encoding" divided by "number of haptic bits before encoding", and the signal-to-noise ratio SNR. The low latency guarantees a lower coding latency, and the corresponding index amounts are the buffering latency and the computation latency. Perceptual lossless means that lossy is allowed, but not perceived by the user, the corresponding index amount is the haptic structure similarity HSSIM.
3. Compared with the existing advanced touch coding method, the high-efficiency low-time-delay kinesthesia signal codec design provided by the invention has the advantages that the compression rate is reduced by 50% on average compared with a dead zone-based touch coding standard algorithm, and meanwhile, the distortion and the time delay are smaller.
Drawings
The invention is described in further detail below with reference to the attached drawings and detailed description:
FIG. 1 is a schematic diagram of a codec structure and a workflow according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a haptic/kinescope signal encoder according to an embodiment of the invention;
FIG. 3 is a schematic diagram of a decoder for haptic/kinescope signals according to an embodiment of the invention;
FIG. 4 is a schematic diagram showing the comparison of a source sequence and a decoded sequence according to an embodiment of the present invention;
FIG. 5 is a diagram of the range of values (node selection) of position signals of a source touch test sequence according to an embodiment of the present invention;
FIG. 6 is a schematic view of the range of values (node selection) of the force signal of the source tactile sensation test sequence according to an embodiment of the present invention;
FIG. 7 is a graph showing compression ratio versus SNR for position signals and force signals according to an embodiment of the present invention;
fig. 8 is a schematic diagram of the compression ratio of the position signal and the force signal of the HSSIM according to an embodiment of the present invention.
Detailed Description
In order to make the features and advantages of the present invention more comprehensible, embodiments accompanied with figures are described in detail below:
as shown in fig. 1, the present embodiment provides a kinescope signal codec with high efficiency and low time delay and a codec method, which comprises an encoder and a decoder:
the modules of the encoder are classified into a signal amplifier, a Discrete Cosine Transform (DCT), a quantizer, run-length encoding, and entropy encoding. The signal passes through each module to generate a code stream as shown in fig. 2.
The blocks of the decoder are divided into entropy decoding, run-length decoding, inverse quantizer, inverse Discrete Cosine Transform (IDCT), and inverse amplifier.
The embodiment adopts three evaluation indexes for the coder and the decoder, which are respectively high efficiency, low time delay and perception lossless.
Specifically, as shown in fig. 2, the workflow of the encoder is as follows:
step a1: for Kinesthetic (Kinesthetic) signals, the sampling frequency is 1000HZ, 8 sampling points are taken for each set of code sequences, and each sampling point value retains 6 bit fractions. The kinesthetic signal employed in this embodiment is a position signal or a force signal. The range of amplitude values of the two kinesthetic signals is smaller, and direct encoding and decoding can lead to larger distortion. To solve this problem, the present embodiment introduces a signal amplifier. The formula of the signal amplifier is shown in (1):
S' ori (i)=S ori (i)M,(I)
wherein S is ori Representing the input of the signal amplifier, i.e. the original signal, S' ori Representing the output of the signal amplifier, M represents the amplification of the signal, in this embodiment, the position signal amplification Mp takes on a value of 200 and the force signal amplification Mf takes on a value of 50.
Step a2: the signal is transformed from the time domain to the frequency domain where most of the energy of the signal is concentrated at a small number of frequencies. The time-frequency domain transformation of the present embodiment adopts a 1-dimensional Discrete Cosine Transform (DCT) algorithm, and the formula is shown in (2), wherein the number of time-domain sampling points n=8:
the first DCT coefficient obtained after DCT transformation is called the direct current coefficient (i.e., DC coefficient), and the last seven DCT coefficients are called the alternating current coefficient (i.e., AC coefficient). The current DC coefficient is predicted from the DC coefficient of the previous coding sequence, and the difference value between the current DC coefficient and the DC coefficient is taken for the subsequent quantization operation. The alternating current coefficient is not predicted, and the current value is directly taken for quantization operation.
Step a3: the DCT transformed output values are quantized, maintaining a high compression rate with less distortion. The formula of the quantizer of this embodiment is shown in (4):
quantized value = DCT coefficient/Q, (4)
Wherein the quantization parameter q= (4,4,16,32,48,64,80,96).
Step a4: the main idea of run-length encoding is to replace a continuous string of identical values with a string length and a representative value for the quantized AC coefficients AC. Thus, the AC coefficient AC has a continuous value of 0, which can be expressed as: (Run, value), where Run represents the number of zero-valued AC coefficients between two nearest non-zero-valued AC coefficients, i.e., run length, and Value represents the magnitude Value of the current non-zero-valued AC coefficient.
In order to represent the code sequence as a bit stream and identify the code length of Value at decoding, it is necessary to rewrite Value to an intermediate state (or transition state), as shown in (5):
Value=(Bits,Value), (5)
where Bits represents the number of Bits needed to store Value. The output DC coefficient and AC coefficient are in the form of: DC (Bits, value) and AC (Run, bits, value).
Step a5: in order to give consideration to two indexes of compression rate and time delay, the entropy coder of the embodiment adopts arithmetic coding, wherein Run and Bits adopt 4-bit fixed length for arithmetic coding, and Value adopts variable length arithmetic coding. Taking DC (0, 0) and AC (0, 1, -1) as examples, decimal to binary conversion is performed. For DC (0, 0), the first 0 is encoded 0000, the second 0 is directly 'empty' without encoding; for AC (0, 1, -1), the first 0 is encoded 0000, the second 1 is encoded 0001, and the third-1 is encoded 0. The binary DC coefficient and the binary AC coefficient are integrated to obtain an encoder output code stream: 0000000000010.
specifically, as shown in fig. 3, the decoder workflow is as follows:
step b1: entropy decoding adopts an inverse algorithm of arithmetic coding, wherein Run and Bits are both inverse algorithms of arithmetic coding with a fixed length of 4 Bits, and Value is inverse algorithms of variable length arithmetic coding.
Step b2: restoring the intermediate state, wherein the formula is shown as (6):
(Bits,Value)=Value, (6)
where Bits represents the number of Bits needed to store the Value.
An inverse algorithm for Run-length encoding is performed in the form of (Run, value), where Run represents the number of zero-Value AC coefficients between two adjacent non-zero-Value AC coefficients and Value represents the magnitude Value of the current non-zero-Value AC coefficient.
Step b3: the formula of the inverse quantizer is shown in (7):
DCT coefficient=quantized value×q, (7)
Wherein the quantization parameter q= (4,4,16,32,48,64,80,96).
Step b4: the formula of the 1-dimensional discrete cosine inverse transformation IDCT algorithm is shown in (8):
wherein n=8 and c (u) is as shown in formula (3).
Step b5: the formula of the inverting amplifier is shown in (9):
wherein S' rec Representing the input of an inverting amplifier S rec Representing the output of the inverse amplifier, i.e. the reconstructed signal, M representing the amplification of the signal, in this embodiment the position signal amplification Mp takes on a value of 200 and the force signal amplification Mf takes on a value of 50.
According to the design of the above codec and method, the present embodiment provides the following evaluation and verification:
step c1: the high efficiency corresponds to objective performance metrics of compression rate (η) and distortion rate. The compression ratio (η) is represented by the formula (10):
wherein B is after Refers to the number of bits of the coded touch signal, B before Refers to the number of haptic signal bits before encoding.
The distortion ratio metric is the signal-to-noise ratio SNR, as shown by equation (11):
where S refers to signal power and B is noise power.
Step c2: the low latency corresponds to an objective performance indicator that is latency. The buffer time delay and the calculation time delay of the coding and decoding algorithm are selected as the measurement standard of the time delay.
Step c3: the perceived lossless corresponds to an objective performance indicator that is a structural similarity. Among them, touch structure similarity HSSIM formula reference Rania Hassen and Eckehard Steinbach.2018.HSSIM: an objective haptic quality assessment measure for force-feedback signs.In 2018Tenth International Conference on Quality of Multimedia Experience (QoMEX). IEEE,1-6.
Step c4: the three evaluation indexes are balanced, namely high efficiency, low time delay and lossless perception. And designing coding parameters according to kinesthesia signal characteristics, designing coding time delay according to a user perception threshold, and balancing three evaluation indexes, so as to realize the balance of compression ratio and reconstruction quality and form a touch signal coder-decoder of the most appropriate application scene.
For verification of the evaluation index, the standard data set of the touch test sequence is adopted in this embodiment, the standard data set provided by IEEE p1918.1.1haptic Codecs Task Group is selected as the source touch test sequence, and 6 segments are taken as total, and represent different touch operations, such as push, pull, drag, beat, etc., respectively, and the test data results are shown in tables 1-6 and correspond to the test result diagrams of fig. 4-8.
TABLE 1
TABLE 2
TABLE 3 Table 3
TABLE 4 Table 4
TABLE 5
TABLE 6
The patent is not limited to the best mode, any person can obtain other various types of high-efficiency low-delay kinesthetic signal codecs and coding and decoding methods under the teaching of the patent, and all equivalent changes and modifications made according to the scope of the patent application are covered by the patent.

Claims (5)

1. A high efficiency low latency kinesthetic signal codec, characterized by: the encoder consists of a signal amplifier, a Discrete Cosine Transform (DCT) module, a quantizer, a run-length coding module and an entropy encoder; the decoder consists of an entropy decoder, a run length decoding module, an inverse quantizer, an Inverse Discrete Cosine Transform (IDCT) module and an inverse amplifier;
the formula of the signal amplifier is as follows:
S′ ori (i)=S ori (i)M,
wherein S is ori Representing the input of the signal amplifier, S' ori Representing the output of the signal amplifier, M representing the amplification factor of the signal;
the discrete cosine transform DCT module adopts a 1-dimensional discrete cosine transform algorithm to transform signals from a time domain to a frequency domain to obtain a direct current coefficient DC and an alternating current coefficient AC; the current direct current coefficient DC is obtained by predicting the direct current coefficient DC of the previous coding sequence, the difference value of the current direct current coefficient DC and the direct current coefficient DC is used for carrying out quantization operation, and the current value of the alternating current coefficient AC is directly taken for carrying out quantization operation;
the method adopts a 1-dimensional discrete cosine transform algorithm to transform a signal from a time domain to a frequency domain, and comprises the following steps of:
the formula of the quantizer is as follows:
quantization value = DCT coefficient/Q;
wherein Q is a quantization parameter;
the run length encoding module performs run length encoding on the quantized alternating current coefficient AC, and is expressed as follows: AC (Run, bits, value), where Run represents the number of zero-valued AC coefficients AC between two nearest non-zero-valued AC coefficients AC, i.e. Run length, bits represents the number of Bits needed to store Value; value represents the magnitude of the current non-zero Value AC coefficient AC or the magnitude of the direct current coefficient DC;
the output DC coefficient DC is: DC (Bits, value);
the entropy coder adopts arithmetic coding, wherein Run and Bits adopt 4-bit fixed length to carry out arithmetic coding, and Value adopts variable-length arithmetic coding;
the entropy decoder adopts an inverse algorithm of arithmetic coding, wherein Run and Bits execute the inverse algorithm of arithmetic coding by using a fixed length of 4 Bits, and Value adopts the inverse algorithm of variable-length arithmetic coding;
the run decoding module restores the intermediate state (Bits, value) to Value and executes an inverse algorithm for run coding;
the formula of the inverse quantizer is as follows:
DCT coefficient = quantization value x Q;
the inverse Discrete Cosine Transform (DCT) module adopts a 1-dimensional DCT algorithm;
the formula of the inverting amplifier is as follows:
wherein S' rec Representing the input of an inverting amplifier S rec Representing the output of the inverting amplifier;
the sampling frequency of the encoder to the kinesthesia signal is 1000HZ, 8 sampling points are taken from each group of coding sequences, and 6 bit decimal values are reserved for each sampling point; the kinesthetic signal is a position signal or a force signal.
2. The high efficiency low latency kinesthetic signal codec of claim 1, wherein:
in the signal amplifier, the value of the position signal amplification factor Mp is 200, and the value of the force signal amplification factor Mf is 50;
in the discrete cosine transform DCT module, the number of time domain sampling points of a 1-dimensional discrete cosine transform algorithm is N=8, the obtained first DCT coefficient is a direct current coefficient DC, and the last seven DCT coefficients are alternating current coefficients AC;
the quantization parameter q= (4,4,16,32,48,64,80,96).
3. The high efficiency low latency kinesthetic signal codec of claim 1, wherein: the coding parameters are determined by kinesthetic signal characteristics, and the coding delay is determined by a user perception threshold.
4. A method for encoding and decoding a kinesthetic signal codec based on the high-efficiency low-latency of claim 1, characterized by: comprises an encoding process and a decoding process;
the encoding process comprises the steps of:
step A1: sampling the kinesthesia signal, and amplifying the sampled signal by a signal amplifier;
step A2: carrying out time domain to frequency domain transformation on the signals by adopting a 1-dimensional discrete cosine transform algorithm to obtain direct current coefficients DC and alternating current coefficients AC;
step A3: carrying out quantization treatment on the output value after the transformation in the step A2;
step A4: run-length encoding is performed on the quantized alternating current coefficient AC, expressed as: AC (Run, bits, value), where Run represents the number of zero-Value AC coefficients between two nearest non-zero-Value AC coefficients, i.e., run length, bits represents the number of Bits needed to store Value; value represents the magnitude Value of the current non-zero Value AC coefficient or the magnitude Value of the DC coefficient;
the output DC coefficient DC is: DC (Bits, value);
step A5: an entropy coder is adopted for arithmetic coding, wherein Run and Bits adopt 4-bit fixed length for arithmetic coding, and Value adopts variable length arithmetic coding;
the decoding process comprises the steps of:
step B1: entropy decoding is carried out on the information obtained by encoding by adopting an inverse algorithm of arithmetic encoding;
step B2: restoring the intermediate state (Bits, value) to Value, and executing an inverse algorithm for run-length coding;
step B3: inverse quantization is carried out on the signals by adopting an inverse quantizer;
step B4: transforming the signal from the frequency domain to the time domain by adopting a 1-dimensional discrete cosine inverse transformation algorithm;
step B5: the signal is reconstructed using an inverse amplifier.
5. The codec method of claim 4, wherein: the sampling frequency of the kinesthesia signals is 1000HZ, 8 sampling points are taken from each group of coding sequences, and 6 decimal places are reserved for the values of each sampling point; the kinesthesia signal is a position signal or a force signal; in the signal amplifier, the value of the position signal amplification factor Mp is 200, and the value of the force signal amplification factor Mf is 50; in the discrete cosine transform DCT module, the number of time domain sampling points of a 1-dimensional discrete cosine transform algorithm is N=8, the obtained first DCT coefficient is a direct current coefficient DC, and the last seven DCT coefficients are alternating current coefficients AC; in the quantization process and the inverse quantization process, the quantization parameter q= (4,4,16,32,48,64,80,96).
CN202011368867.4A 2020-11-30 2020-11-30 High-efficiency low-time delay kinescope signal coder-decoder and coding-decoding method Active CN112564713B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202011368867.4A CN112564713B (en) 2020-11-30 2020-11-30 High-efficiency low-time delay kinescope signal coder-decoder and coding-decoding method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202011368867.4A CN112564713B (en) 2020-11-30 2020-11-30 High-efficiency low-time delay kinescope signal coder-decoder and coding-decoding method

Publications (2)

Publication Number Publication Date
CN112564713A CN112564713A (en) 2021-03-26
CN112564713B true CN112564713B (en) 2023-09-19

Family

ID=75045163

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202011368867.4A Active CN112564713B (en) 2020-11-30 2020-11-30 High-efficiency low-time delay kinescope signal coder-decoder and coding-decoding method

Country Status (1)

Country Link
CN (1) CN112564713B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114023020B (en) * 2021-10-29 2023-06-30 福州大学 Touch data hybrid compression system based on data characteristics and improved regression

Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5706002A (en) * 1996-02-21 1998-01-06 David Sarnoff Research Center, Inc. Method and apparatus for evaluating the syntax elements for DCT coefficients of a video decoder
CN1195930A (en) * 1997-03-14 1998-10-14 诺基亚流动电话有限公司 Audio signal coding method and apparatus
CN1198613A (en) * 1997-04-02 1998-11-11 三星电子株式会社 Digital data coding/decoding method and equipment thereof
KR19980075637A (en) * 1997-03-31 1998-11-16 이준우 Quantization and Dequantization Device for Compression and Restoration of Image Signal
JP2001258029A (en) * 2000-03-10 2001-09-21 Matsushita Electric Ind Co Ltd Method and system for dynamically displaying residue coefficient
JP2002044662A (en) * 2000-07-24 2002-02-08 Sony Corp Data encoder and encoding method and data decoder and decoding method
KR20040063650A (en) * 2003-01-08 2004-07-14 엘지전자 주식회사 Video resizing system of video codec
CN1656690A (en) * 2002-04-02 2005-08-17 诺基亚有限公司 Coding transform coefficients in image / video encoder and/or decoders
CN101267563A (en) * 2002-01-22 2008-09-17 诺基亚有限公司 Adaptive variable length coding
CN101443842A (en) * 2006-05-12 2009-05-27 弗劳恩霍夫应用研究促进协会 Information signal coding
CN111835364A (en) * 2020-08-03 2020-10-27 辽宁工程技术大学 Low-complexity nerve BP decoding method for polarization code

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6757439B2 (en) * 2000-12-15 2004-06-29 International Business Machines Corporation JPEG packed block structure
US7275036B2 (en) * 2002-04-18 2007-09-25 Fraunhofer-Gesellschaft Zur Foerderung Der Angewandten Forschung E.V. Apparatus and method for coding a time-discrete audio signal to obtain coded audio data and for decoding coded audio data
US20080008395A1 (en) * 2006-07-06 2008-01-10 Xiteng Liu Image compression based on union of DCT and wavelet transform

Patent Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5706002A (en) * 1996-02-21 1998-01-06 David Sarnoff Research Center, Inc. Method and apparatus for evaluating the syntax elements for DCT coefficients of a video decoder
CN1195930A (en) * 1997-03-14 1998-10-14 诺基亚流动电话有限公司 Audio signal coding method and apparatus
KR19980075637A (en) * 1997-03-31 1998-11-16 이준우 Quantization and Dequantization Device for Compression and Restoration of Image Signal
CN1198613A (en) * 1997-04-02 1998-11-11 三星电子株式会社 Digital data coding/decoding method and equipment thereof
JP2001258029A (en) * 2000-03-10 2001-09-21 Matsushita Electric Ind Co Ltd Method and system for dynamically displaying residue coefficient
JP2002044662A (en) * 2000-07-24 2002-02-08 Sony Corp Data encoder and encoding method and data decoder and decoding method
CN101267563A (en) * 2002-01-22 2008-09-17 诺基亚有限公司 Adaptive variable length coding
CN1656690A (en) * 2002-04-02 2005-08-17 诺基亚有限公司 Coding transform coefficients in image / video encoder and/or decoders
KR20040063650A (en) * 2003-01-08 2004-07-14 엘지전자 주식회사 Video resizing system of video codec
CN101443842A (en) * 2006-05-12 2009-05-27 弗劳恩霍夫应用研究促进协会 Information signal coding
CN111835364A (en) * 2020-08-03 2020-10-27 辽宁工程技术大学 Low-complexity nerve BP decoding method for polarization code

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
Shih-Hsuan Yang,Po-Feng Ch.Error Resilience and Error Concealment for Embedded Wavelet Coders .Error Resilience and Error Concealment for Embedded Wavelet Coders .2015,1-7. *
张维纬.中国博士学位论文全文数据库.2013,(01),1-100. *
转置容错熵编码;尹明亮, 方 勇;计算机工程与设计;第35卷(第12期);4264-4269 *

Also Published As

Publication number Publication date
CN112564713A (en) 2021-03-26

Similar Documents

Publication Publication Date Title
KR101176691B1 (en) Efficient coding and decoding of transform blocks
CA2618564C (en) Adaptive coding and decoding of wide-range coefficients
KR100529311B1 (en) Apparatus and method for selecting the length of variable length coding bit stream using neural network
Padmaja et al. Analysis of various image compression techniques
TW200828268A (en) Dual-transform coding of audio signals
WO2020237646A1 (en) Image processing method and device, and computer-readable storage medium
CN103489203A (en) Image coding method and system based on dictionary learning
CN102138326A (en) Method and apparatus for inverse quantizing image, and method and apparatus for decoding image
KR20190040063A (en) Quantizer with index coding and bit scheduling
WO1995009487A1 (en) High efficiency encoding/decoding device
CN112564713B (en) High-efficiency low-time delay kinescope signal coder-decoder and coding-decoding method
WO2011137841A1 (en) Method and device for compression encoding, method and device for decompression decoding, and communication system
JP4163680B2 (en) Adaptive method and system for mapping parameter values to codeword indexes
CN102572426B (en) Method and apparatus for data processing
Mahmud An improved data compression method for general data
JPWO2010074200A1 (en) Coding apparatus and decoding apparatus for adaptive differential pulse code modulation
JP3557164B2 (en) Audio signal encoding method and program storage medium for executing the method
JP4918103B2 (en) Encoding method, decoding method, apparatus thereof, program, and recording medium
Alexandre et al. Learned image compression with soft bit-based rate-distortion optimization
US6819800B2 (en) Moving image compression/decompression apparatus and method which use a wavelet transform technique
CN114023020B (en) Touch data hybrid compression system based on data characteristics and improved regression
KR20030090376A (en) Method of bitplane encoding and decoding using graycode and apparatus using thereof
Krishnanaik et al. Implementation of wavelet transform, DPCM and neural network for image compression
CN116723333B (en) Layered video coding method, device and product based on semantic information
JP2019504340A (en) Audio encoding using video information

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant