1 简介
摘要:
The purpose of image fusion is to merge relevant information from multiple images right into a single image. In this paper, by conducting the review it has been discovered that the majority of the existing techniques are based upon transform domain therefore it could results in some artifacts which might decrease the execution of the transform based vision fusion techniques. Moreover it is already been discovered that the issue of the uneven illuminate has already been neglected in the absolute most of existing focus on fusion. Therefore to overcome these issues, a fresh method which integrates the larger valued Alternating Current (AC) coefficients calculated in iterative block level principal component averaging (IBLPCA) domain base fusion with illuminate normalization and fuzzy enhancement has been proposed in this paper. The experimental results show the efficiency of proposed algorithm over existing work.
2 部分代码
%function[] = DDCTIFdemo()% DDCT (Directional Discrete Cosine Transform) based image fusion - demo% VPS Naidu, MSDF Lab, CSIR-NAL, March 2014% Reference: "?% Journal of Optics, Vol. 43, No.1, pp.48-61, March 2014.%%close all;clear all;home;%%dflg = 1; % 0: no display OR 1: displayaflag = 1; % 1: Average, 2: max rule OR 3: energy rulebs = 4; %[4 8 16 32 64 128 256]; block size%%% insert imagesimt = im2double(imread('saras9t.jpg'));im1 = im2double(imread('saras91.jpg'));im2 = im2double(imread('saras92.jpg'));if dflg == 1figure(1);subplot(121);imshow(im1);title('image to be fused - im1');subplot(122);imshow(im2);title('image to be fused - im2');pause(1);end%%mode = [0 1 3 4 5 6 7 8]; % directional modelmode = length(mode);%%if aflag == 1 % fusion by DDCT average ruleh1 = waitbar(0,'Please wait...');for j=1:lmodeimf1{j} = DDCTIFav(im1,im2,bs,mode(j));waitbar(j/lmode,h1);endclose(h1);end%%if aflag == 2 % fusion by DDCT max ruleh1 = waitbar(0,'Please wait...');for j=1:lmodeimf1{j} = DDCTIFmax(im1,im2,bs,mode(j));waitbar(j/lmode,h1);endclose(h1);end%%if aflag == 3 % fusion by DDCT energy ruleh1 = waitbar(0,'Please wait...');for j=1:lmodeimf1{j} = DDCTIFek(im1,im2,bs,mode(j));waitbar(j/lmode,h1);endclose(h1);end%%% fusion by PCAimf = fuse_pca(imf1{1},imf1{2},imf1{3},imf1{4},imf1{5},imf1{6},imf1{7},imf1{8});%%% Performance evaluation metrics[RMSE,SF] = im_fuse_per_eval(imt,imf);%%% display resultsif dflg == 1figure(2);subplot(121); imshow(imf); title('fused image');imd = imt-imf;subplot(122); imshow(imd); title('error image');endfprintf('\nRMSE : %3f2', RMSE);fprintf('\nSF : %3f2', SF);fprintf('\n\n');%%
3 仿真结果

4 参考文献
[1]赵晓雷. 基于IHS变换和主成分分析变换的图像融合[J]. 科学技术与工程, 2010(20):4.
[2] Kaur P . Hybrid PCA-DCT Based Image Fusion For Medical Images.
博主简介:擅长智能优化算法、神经网络预测、信号处理、元胞自动机、图像处理、路径规划、无人机等多种领域的Matlab仿真,相关matlab代码问题可私信交流。
部分理论引用网络文献,若有侵权联系博主删除。
该文提出了一种结合迭代块级主成分平均(IBLPCA)域中较大值交流(AC)系数、光照归一化和模糊增强的新图像融合方法。实验结果显示,所提算法优于现有技术。代码示例展示了基于方向离散余弦变换(DDCT)的融合规则,包括平均、最大和能量规则。此外,还提供了性能评估指标和参考文献。
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