图片（信息熵、对比度、平均亮度、清晰度）

该matlab代码实现了plsa算法。plsa全称是概率隐语义分析，是一个非常重要的隐语义分析模型。(This matlab code implements plsa algorithm, which is the short of probability latent semantic analysis and is a very important latent semantic analysis model.)

说明：  针对现有方法存在的隐藏容量低、操作不灵活的缺陷，文章提出了一种基于无损压缩的加密图像可逆 信息隐藏算法。(In view of the defects of low hiding capacity and inflexible operation of the existing methods, this paper proposes a reversible information hiding algorithm for encrypted images based on lossless compression.)

这些程序可以将MSTAR数据库中的数据转换为可是图像，例如JPEG和TIFF，方便SAR图像的处理。(These program can convert the MSTAR data into some images such as jpeg and tiff.It s easy to study sar images.)

基于光线补偿的人脸检测。首先对图像进行光补，在此基础上结合肤色和发色进行人脸检测。(Light compensation based on face detection. First, the image light make up, in this based on the combination of color and hair color for face detection.)

速度匹配传递对准，matlab,仿真程序(Speed ​ ​ matching transfer alignment, MATLAB simulation program)

稀疏矩阵的实例，讲述如何用稀疏矩阵进行实际的编程。本例是以超市购物为实际背景。(Examples of sparse matrix)

图割（GC)和主动轮廓模型（ACM)相结合的一种图像分割方法，既可以进行局部图像的分割，也可进行全局图像的分割，简单实用。(A combination of graph cuts (GC) and the active contour model (ACM) image segmentation method, either local image segmentation, global image segmentation, simple and practical.)

说明：  《数字图像处理与机器视觉:Visual C++与Matlab实现》5 图像分割,霍夫变换,Hough变换直线检测的Matlab实现(&quot Digital image processing and machine vision: Visual C++ and Matlab to achieve&quot 5 image segmentation, Hough transform, Hough transform line detection of the Matlab implementation)

此程序在时域中进行阈值去噪，基于平均阈值的去噪方法(This procedure carried out in the time domain threshold denoising, based on the average, the threshold de-noising method)

针对CT 医学图像和MR I 医学图像成像特点, 提出了基于快速整数提升小波变换的融合方法。在CT 和 MR I 两幅医学图像配准的前提下, 利用提升小波变换把图像分解成低频和高频子图像, 对于小波变换后的高频 子图像, 选择区域标准差大的作为融合后的子图像 对于低频子图像, 采用加权融合, 最后进行小波逆变换, 得到 融合后的图像, 并对融合后图像用信息熵、平均梯度、相关系数的指标进行评价。实验结果表明, 基于快速整数提 升小波变换融合中, 小波高低频系数采用不同的规则能够取得更好的融合效果, 其轮廓清晰。该算法能够提升融 合后的医学图像信息量, 同时有效地保护图像的细节信息, 在执行时间和图像质量上均优于普通小波算法。(A imed at the characterist ics of CT andMR Imedical images, a new image fu sion al2 go rithm based on the fast in t lif t ing w avelet t ran sfo rm s is p ropo sed. Two o riginal images are decompo sed by the fast in t lif t ing w avelet t ran sfo rm s. The fu sion ru le based on the max imum standard deviat ion value variance is u sed to fu se the h igh f requency sub2image, w h ile a w eigh t2 ed average fu sed ru le is app lied by coeff icien t s of the low f requency. F inally, the fu sion image is recon st ructed fo r perfo rm ing inverse fast in t lif t ing w avelet t ran sfo rm s. The fu sion image is evaluated by en t ropy, average gradien t, and co rrelat ion coeff icien t s. Experimen tal resu lt show s that the fu sion image hasmo re info rmat ion than o riginal images and imp roves the quali2 ty of o riginal images. M eanw h ile, the fu sion image p ro tect s detail characterist ics of the image, thu s the real2t ime p rocess and image qualit ies are w ell than tha)