This repository contains my assignment solutions for the Digital Image Processing course (M2608.001000_001) offered by Seoul National University (Fall 2020).
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Updated
Apr 11, 2022 - MATLAB
This repository contains my assignment solutions for the Digital Image Processing course (M2608.001000_001) offered by Seoul National University (Fall 2020).
Consider an image which is corrupted by both additive Gaussian noise and defocus blur. Here I have implemented a Wiener filter to restore the image to make it less noisy and less blurry. To evaluate the restored image I use PSNR (Peak Signal to Noise Ratio).
Adaptive Signal Processing (2020 Fall)
Labs of DSP2
This project was done in partial fulfillment of the requirements for the module JEB 1444: Neural Engineering in Winter 2023. First, the FitzHugh-Nagumo model is used to explore the dynamics of a coupled system and generate input-output relationships. Secondly, Wiener Bose Model is used to learn a non-parametric model on input-output signals.
Digital image processing Algorithms and their application to the real problems.
Exercises for my Signal Processing course
Digital Image Processing written in MATLAB.
Matlab implementation of Wiener Filter and Lms Adaptive Filtering
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