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Novel image compression–encryption hybrid algorithm based on key-controlled measurement matrix in compressive sensing

Python 100.00%

compressive-sensing encryption compression research

ceha's Introduction

comp6771

Introduction

Project implementing the paper titled Novel image compression–encryption hybrid algorithm based on key-controlled measurement matrix in compressive sensing by Nanrun Zhou, Aidi Zhang, Fen Zheng, and Lihua Gong.

Set-up

The following is required to run the project.

Python 3.6
numpy
scipy
matplotlib
opencv

I suggest installing using Anaconda. First, download Anaconda and install it.

Then, in command line, run the following:

conda create -n py37 python=3.7

activate py37

conda install numpy scipy matplotlib opencv

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ceha's Issues

Implement random pixel exchanging

Implement a function to randomly swap pixels between the 4 quadrants.

This function should take two matrices as input I_1 and I_2. It should then swap pixels between them according to the algorithm described in the paper.

Implement Φ

Write a function to generate the function Φ based on the logistic map

Implement image read + splitting

Write two functions:

read the input image using OpenCV, verify size constraints.
split the image into 4 matrices.

Implement compressive sensing

Write a function to implement the compressive sensing algorithm described in the paper.

It should take as input:

Measurement matrix phi
input x
desired domain, psi

Implement pseudo-random logistic map

Implement a function to generate the logistic map.

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