HeKaiming_hazeremoval_CN_Matlab

c++特征提取，提取图像当中的红色灯笼。。。(c++ feature extraction, image extraction among red lanterns)

：数字水印技术作为数字媒体版权保护的有效办法，近年来在国内外引起了人们极大的兴趣。作者采用了DCT离散余弦变换的算法，对图像这种多媒体数字作品进行了数字水印的嵌入和检测研究。并且使用了高效实用的编程工具MATLAB来介绍了一种DCT域的图像数字水印嵌入和提取的(BASIC_WM.M ..........................................cellauto.m ..........................................dctwatermark.m ..........................................detectbasic_wm.m ..........................................plotcorr_coef.m ..........................................wavedetect.m ..........................................wavedetect2.m ..........................................wavemarksvd.m ..........................................wavemarksvd)

图像的傅里叶变换。在代码中实现了将两幅图像的幅度谱和相位谱进行交换，进而理解两者在图像显示中的作用(Fourier transform of the image. Implemented in the code will be two images amplitude spectrum and phase spectrum of exchange, and thus to understand both the role of the image display)

实现简单图像处理，包括256色转灰度图、Hough变换、Walsh变换、中值滤波、二值化变换、亮度增减、傅立叶变换、反色、取对数、取指数、图像平移、图像旋转、图像细化、图像缩放、图像镜像、均值滤波、对比度拉伸、拉普拉斯锐化（边缘检测）、方块编码、梯度锐化、灰度均衡、直方图均衡、离散余弦变换、维纳滤波处理、逆滤波处理、阈值变换、高斯平滑。(simple image processing, including color to grayscale 256, the Hough transform, Walsh transform, Median filtering, binary conversion, brightness changes, Fourier transform, and color-from the few to admit index, image shifting, image rotation, refined images, image scaling, image mirroring, mean filtering, contrast stretching, Laplacian sharpening (edge detection), block codes, Sharpening gradient, gray balance, histogram equalization, discrete cosine transform, Wiener filter, reverse filtering, threshold transform, Gaussian smoothing.)

傅里叶变换及其逆变换的基于VC6.0实现(Fourier transform and its inverse transform)

IDL语言进行波段运算功能的源代码，有两个内容(IDL language band math )

说明：  一种比较实用的sar影像边缘检测算法，谢谢大家交流(A practical edge detection algorithm for SAR images. Thank you for your communication.)

本程序和实现对一幅包含人脸的bmp图像进行光纤补偿，对人脸区域进行检测实现人眼和人嘴的检测与定位，最后勾绘出人脸的特征以实现人脸检测的目的。(This procedure and implementation of a compensate the fiber contains face of BMP image, the face region detection to realize human eyes and mouth detection and positioning, finally drew out the facial features to achieve the purpose of face detection. )

说明：  SIFT的MATLAB源码，由加州大学的一位博士编写。(SIFT the MATLAB source code, from the University of California, prepared by Dr. A.)

用协方差方法估计AR模型参数,进而实现功率谱估计,()