|
EDA365欢迎您登录!
您需要 登录 才可以下载或查看,没有帐号?注册
x
' b" E4 ^- w! x X: K5 A. X% F+ V
一、简介7 V5 `0 E3 I! Q" Q
图像增强是一种必要的和不可缺少的技术,增加数字的质量图像。的主要任务是生成一个新的图像中每个像素强度值使用转换函数在输入图像接收每个像素的强度值。拟议的传递函数研究被称为区域相似性传递函数(RSTF)认为密度分布相似相邻像素之间。蜻蜓算法(DA)直观的优化技术,这是首选工程应用中,已被用于优化提出了传递函数的参数值。' _$ G; ], C5 @5 @+ Q
5 c7 o# k/ E7 n w& a' Q二、源代码
( m( O4 V+ J$ O6 S 7 B6 W, G5 N; U+ \, I
- % Using the Regional Similarity Transformation Function and Dragonfly Algorithm.
- %%%%%%%%%%%%%%%%%%%%%%%%%%%%
- %THIS IS A DEMO FOR NOVEL IMAGE ENHANCEMENT USING GRAV脻TAT脻ONAL SEARCH ALGORITHM
- clc;
- clear all;
- close all;
- %READ IMAGE
- i=imread('test5.bmp');
- i=imresize(i,1);
- %--------------------------------------------------------------------------
- %GLOBAL MEAN
- frekans=zeros(256,1);
- % It records by counting how many times each pixel value is.
- for k=1:size(i,1)
- for l=1:size(i,2)
- value=i(k,l);
- frekans(value+1)=frekans(value+1)+1;
- end
- end
- deger=max(frekans);
- for k=1:256
- if deger==frekans(k)
- D=k;
- end
- end
- D=double(D/255);
- image = im2double(i);
- global_mean = D;
- %--------------------------------------------------------------------------
- % LOCAL MEAN
- Bmean = mean_n(image);
- %--------------------------------------------------------------------------
- %SIMILARITY
- [S]=similarity(i);
- B=double(S);
- %--------------------------
- C = std_n(image,Bmean);
- im_size = size(image);
- %-------------------------------------------------------------------------
- %OPTIMIZATION PARAMETERS
- N=15; % Agent number;
- Max_iteration=15;
- %-------------------------------------------------------------------------
- %CALL FUNCTION
- [parameters Fbest BestChart MeanChart] = GSA_enhancement2(image,global_mean,B,C,im_size, N, Max_iteration);
- enh = trans(i,image, B, C, global_mean, parameters(1),parameters(2),parameters(3),parameters(4) );
- figure;
- subplot(121)
- imshow(image);
- title('原图')
- subplot(122)
- imshow(enh);
- title('GSA增强后的灰度图')
/ G0 h4 I% ]% o) ?/ P7 M/ u
l* V' [: o/ K4 _
7 R! K3 j( W. v# ~$ I8 ?1 k
6 M; P1 O3 ^" r# n8 G' G
|
|