image_enhance下载

weixin_39821260 2019-09-19 02:00:47

DIP作业，基于空间域的图像增强。gamma变换，平滑滤波，拉普拉斯锐化，sobel边缘提取。
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AUTOENHANCE Automatically adjusts/enhances the image(brightness, color and contrast) to "optimum" levels.

BIOMEDICAL SIGNAL AND IMAGE PROCESSING The main goal of the thesis is to show the de-noising algorithms based upon the discrete wavelet transform (DWT) that can be applied successfully to enhance noisy multidimensional magnetic resonance (MR) data sets i.e two-dimensional (2-D) image slices and three-dimensional (3-D) image volumes

fuzzy logic image enhacement it s an advanced codes to enhance images using type 2 fuzzy logic and intuitionistic fuzzy sets

Infrared image enhancement is a crucial technique for improving the quality of infrared images. And, the clear image details are important information for infrared image analysis. To effectively enhance infrared image and make image details clear, a multi-scale sequential toggle operator based algorithm is proposed in this paper. Firstly, the sequential toggle operator, which uses opening and closing as primitives, is con- structed and discussed. Secondly, the feature extraction in infrared image through the sequential toggle operator is given, and the multi-scale extension of the feature extraction is discussed in details. Finally, the extracted final

不怎么实用，希望各位批评指导，相互学习 clear all,close all, TestDatabasePath = uigetdir('E:\我的大学', 'Select test database path');%自己设置地址 prompt = {'Enter test image name:'}; dlg_title = 'finger Recognition System'; num_lines= 1; def = {'1'}; TestImage = inputdlg(prompt,dlg_title,num_lines,def); TestImage = strcat(TestDatabasePath,'\',char(TestImage),'.bmp'); im = imread(TestImage); tic I=imresize(im,[200 200]); figure(1),subplot(131),imshow(I),title('原图'); set(gcf,'position',[1 1 600 600]); level=graythresh(I); J=im2bw(I,level); figure(1),subplot(132),imshow(J),title('二值图');

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