[image denoising] image denoising based on nonlocal Euclidean median (nlem) with matlab code

1 brief introduction

With the development of Industrial Technology , There are more and more digital image acquisition devices , The application environment of digital image is more and more extensive . Digital images in medicine 、 space flight 、 military 、 meteorological 、 Media and many other fields play a decisive role . Because the image is inevitably polluted by noise in the process of acquisition and transmission , therefore , Image denoising is a key step in image processing .

The denoising effect also directly affects the image analysis 、 Identification and other follow-up tasks . The purpose of image denoising is to keep the useful details of the image as much as possible , By removing noise , To get a more realistic image . Today, , Whether in academia or industry , Image denoising is a research hotspot .

2 Part of the code

%%denoising demo using Non-Local Euclidean Medians (NLEM)%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%  img      : clean grayscale image%  h        : width of Gaussian%  P        : half-size of patch %  S        : half-search window %%  Author:    Kunal N. Chaudhury%  Date:      June 10, 2012%%  Reference: %  K. N. Chaudhury, A. Singer, "Non-Local Euclidean Medians", IEEE Signal%  Processing Letters, vol. 19, no. 11, 2012. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%​clc; clear all; close all force;​% clean imageimg    = double(imread('ckb.jpg'));[m, n] = size(img);​% add noisesigma     =  70;imgNoisy  =  img  +  sigma * randn(m,n);​% NLEM parametersS  = 10;P  = 3;h  = 10 * sigma;​% call NELM (or NLEM_kNN)imgDenoised = NLEM(imgNoisy, h, P, S);​​% show resultspeak  = max(max(img));PSNR0 = 10 * log10(m * n * peak^2 / sum(sum((imgNoisy - img).^2)) );PSNR1 = 10 * log10(m * n * peak^2 / sum(sum((imgDenoised - img).^2)) );​figure();colormap gray,subplot(1,3,1), imagesc(img), title('Original', 'FontSize', 10), axis('image', 'off');subplot(1,3,2), imagesc(imgNoisy), title([ 'Noisy, ', num2str(PSNR0, '%.2f'), 'dB'] , 'FontSize', 10), axis('image', 'off');subplot(1,3,3), imagesc(imgDenoised), title([ 'NLEM filtered, ', num2str(PSNR1, '%.2f'), 'dB'] , 'FontSize', 10),axis('image', 'off');​

3 Simulation results

4 reference

[1] Sunzhonggui . Research and application of nonlocal mean filter [D]. Nanjing University of Aeronautics and Astronautics .

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