SusanCorner

说明：  数字图像处理中非常有用的一些图片包括LENA等.(Digital image processing is very useful in a number of pictures, including LENA, BARBARA such.)

图像剧烈湍流模糊，数字图像处理（第二版）第五章例题5.25的实现程序(Severe turbulence fuzzy image, digital image processing (second edition), Chapter V, Example 5.25, to achieve program)

对嵌入水印的图象进行不同的攻击 添加噪音，滤波，剪切，压缩，旋转45度(Watermark on the images embedded in a different attack to add noise, filter, shear, compression, rotating 45 degrees)

该软件可实现图像间格式的转换,主要实现: (e)ps,bmp, jpg, png,tif,gif, psdi图像格式之间的转换(The software enables format conversion between images, the main achievement: (e) ps, bmp, jpg, png, tif, gif, psdi image format conversion between)

这些代码主要是IDL语言源码，主要功能：初始化ENVI,定标,大气校正,融合,镶嵌,裁剪,分类(监督+非监督),面向对象特征提取,结束ENVI(These codes are mainly IDL language source code, the main functions: initialization, ENVI, calibration, atmospheric correction, fusion, mosaic, cutting, classification (supervision + non supervision), object oriented feature extraction, ending ENVI)

说明：  利用97小波变换进行图像压缩，用matlab仿真，实验证明它具有较高的压缩比(using wavelet transform image compression using Matlab simulation experiment to prove that it has a higher compression ratio)

快速的Lee滤波算法，代码经过优化，修正和测试，能有效减少SAR图像中的斑点噪声。(Fast Lee filter algorithm, code optimized, modification and testing, can effectively reduce the SAR image speckle noise.)

otsu s multilevel thresholding method

基于颜色特征向量的粒子滤波跟踪程序，修复了因粒子超过窗口范围出现ERROR的BUG，还包括了一些有助于粒子滤波学习的资料！！(color-based particle filter tracking, some bugs have been fixed, some information about PF Tracking is included too!!)

图像分割是把图像划分成具有实际意义的互补交迭的区域的集合。在图像分割之前，图像区域的数目未知，而在分割后各个区域同时满足均匀性和连通性的条件，故图像分割是一个复杂的过程，目前大多数研究都是针对某一类型图像或者某一具体应用的分割。图像阈值化分割的基本思想是确定一个阈值，然后把每个像素点的像素值和阈值相比较，根据比较的结果把像素划分为两类，前景(1)或背景(0)。该方法的关键是确定一个最优的阈值。常用的阈值确定方法有直接门限法、类间最大方差法(otsu法)、分水岭算法、最小误差法、最大熵法等。该段代码就是图像的阈值分割。(The image segmentation is divided into the practical significance of the emerging area of complementary set. In the image segmentation, before the number of image region, the unknown, and after each area in division at the same time satisfy the uniformity and connectivity condition, so the image segmentation is a complicated process now, most research are for a certain type image or a particular application of the division. Image threshold segmentation of the basic idea is to determine a threshold, then put each pixel threshold value of the pixels and compared, according to the result of the comparison the pixel divided into two categories, the prospect (1) or background (0). This method is the key to determine an optimal threshold. Commonly used method to determine the threshold value of direct threshold method, the largest of the variance between method (otsu method), watershed algorithm, the minimum error method, the maximum entropy method, etc. When the code is image threshold segm)