12148086KSVD_Matlab_ToolBox

说明：  MIT的人脸数据库，包括人脸和非人练部分。(face database from MIT)

其中用到了 timer控件

应用Matlab写的HDR图像处理完整工具，包括：合成HDR图像、TMO等，路径完整，亦包括示例、例图。非常有用的学习工具。(It s a totally codes of HDR image processing, including HDRI generation, TMO, etc. Very useful tool for study.)

基于差值的可逆水印算法源码，及详解说明。还包括一篇英文论文和该作者的一些理解和解释，希望对大家有帮助(Reversible watermarking algorithm based on difference of source code, and the Detailed Description. Also includes an English papers and some of the author' s understanding and interpretation, we hope to help)

一种采用中心环绕函数进行的retinex算法，可以对于暗视觉的图像进行有效的增强(A center around the functions of the Retinex algorithm, can for scotopic vision image effectively enhanced)

1．选择一幅图像，对该图像进行DCT块操作（将图像分成8×8小块，对每个小块进行DCT变换）。 2.利用屏蔽矩阵对DCT系数进行区域选择，然后进行逆变换（IDCT），合成原图像，计算合成图像的PSNR。 3.选择一小波函数，对一幅图像进行分解，显示各变换系数，观察其规律，并进行小波逆变换，合成原图像。 (1. Select an image, the image DCT block operations (the image is divided into 8 × 8 small pieces of each small piece for DCT transform). 2. The use of shielding on the DCT coefficient matrix of regional choices, and then inverse transform (IDCT), synthesis of the original image, calculating the synthetic image PSNR. 3. To select a wavelet function, decomposition of an image to show the transform coefficients, to observe its laws, and inverse wavelet transform, the original synthetic image.)

利用小波实现图像的融合，从两幅模糊的原始图像中回复出原来的图像(Using wavelet analysis for a given image enhancement processing, after the decomposition of image, contour by the low frequency part representation, characterization details with high frequency part. )

用MATLAB实现将灰度图像转换为伪彩色图像。(Convert grayscale images to RGB using specified colormap.)

基于SUSAN特征检测算子的边缘提取，添加图片即可运行，可自行根据图片特征设置参数得到较好的边缘检测效果(Edge detection feature extraction SUSAN operator, add images to run, you can set your own parameters to get a better edge detection based on image characteristics)

整合了不完整张量的平滑平行因子分解和最小化张量秩模型的有效选择的张量补全，用于图像处理，(The proposed method admits significant advantages, owing to the integration of smooth PARAFAC decomposition for incomplete tensors and the efficient selection of models in order to minimize the tensor rank.)