# DSP2-PROJECT

**Repository Path**: cmystal_space/DSP2-PROJECT

## Basic Information

- **Project Name**: DSP2-PROJECT
- **Description**: This project is aim to use different optimization method to do image denoising based on total variation denoising.
- **Primary Language**: Python
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2019-01-22
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# DSP2-Final Project:Different Optimization Method to Implement Total Variation Denoising
This project is aim to use different optimization method to do image denoising based on total variation denoising.
* To run these codes, install numpy,matplotlib,scipy,PIL,skimage packages.
* In this project, the original image is Lena512 which is often used in image processing. Add normal distributed noise to the image and do 
  TVD denoising.
# Packages used in project 
* The linear_operator.py and proximal_operator.py defines some function of processing data. Cost_function.py defines the function to         calculate the cost of the model we choose in iamge processing.

* denoise_tv_chambolle.py uses the chambolle method to do denoising.

* denoise_tv_gradient.py is based on the gradient descent model, and I design this method only based on mathematical way and assume the     image has constinuous value, this is an approximate method to do denoising.

* denoise_tv_rof_primal_dual.py is based on primal-dual algorithm which is widely used in optimization. This method is based on rof model   and it shows great ability to denoise normal distributed noise in image processing.

* denoise_tv_fista.py is also based on primal_dual algorithrm and it use different optimization method to reach the optimal denoisd         result. Usually it has fewer iterations to get covergence.



# Dependencies:
1. scipy, numpy, matplotlib



# References
* 1.Fast Gradient-Based Algorithms for Constrained Total Variation Image Denoising and Deblurring Problems.  Amir Beck and Marc Teboulle
* 2.A Tutorial on Primal-Dual Algorithm.                                                                     Shenlong Wang
* 3.ROF and TV-L1 denoising with Primal-Dual algorithm.                                                      Alexander Mordvintsev
* 4.An introduction to Total Variation for Image Analysis.                                                   Antonin Chambolle, Vicent                                                                                                                  Caselles, Matteo Novaga,                                                                                                                  Cremers, Thomas Pock, Daniel