matlab

Gray Level Edge Thinning Method Abstract. An effective edge thinning algorithm is important in image segmentation and object identification since it increases the possibility of success in detecting objects in the image and saves the processing time in the further steps such as labeling and image transformation. We investigate some gray level edge thinning method that is based on the gradient magnitude within 3x3 local neighborhood. The new method has been tested with various types of images the real world. Experimental results show that this method produces more accurate images than those of the popular non-maximum suppression methods do.

利用matlab，对图像进行高斯滤波，然后通过非极大值抑制，设置双阈值，实现图像边缘检测(Image edge detection)

说明：  何凯明图像去雾的算法MATLAB实现 以及改进(He kaiming image defogging algorithm MATLAB implementation and improvement)

修复破损图片，图像修复序列-Lowrank模型(Repair damaged picture, image repair sequence -Lowrank model)

图像经过小波变换之后提取子带系数源代码在MATLAB中的实现(subbands in matlab)

基于OTSU算法的图像分割工具，有原汁原味的OTSU和改进，可以作比较 (OTSU algorithm based on image segmentation tool, there is authentic OTSU and improvements can be compared)

图像融合评价程序，通过均值，标准偏差，熵，梯度，相关系数，光谱扭曲度等多个指标对融合图像进行评价比较。(image fusion evaluation procedures, the mean, standard deviation, entropy, gradient, and the correlation coefficient. spectral distortion degree of integration of various indicators to evaluate the comparative images.)

用方向可调小波变换实现图像边缘提取，包涵实验报告及原图像及处理结果(Steerable Wavelet Transform using edge extraction, bear with lab reports and the original image and processing results)

本工程收集了多种常用条码的生成方法

用于评价图像分割算法性能的代码，包中的word文档对所用方法进行了简单的说明，还列出了具体的参考文献(Image segmentation algorithm for evaluating the performance of the code, including the word document on the methods for a simple explanation, but also a list of specific references)