compute_E

说明：  用于显著性检测的对比算法SP的MATLAB版本，比较新的是2013年的，亲测可用(MatLAB version of SP, a contrast algorithm for saliency detection, is relatively new in 2013, and pro-test is available.)

一种比较新颖的方法，通过对以往提出几种核估计方法的融合，建立新核，达到更好的图像恢复效果(A relatively new method, proposed in the past by the nuclear fusion of several estimation methods, the establishment of new nuclear, to achieve better image restoration effect)

说明：  在稀疏域中，基于迭代阈值的线性反转问题，Daubechies 的经典外文文章，用于压缩感知(In the sparse domain, iterative threshold-based linear inversion problem, Daubechies classic foreign language articles for compressed sensing)

DWT域的水印提取，matlab 以及信噪比分析(DWT watermark extraction, and signal-to-noise ratio analysis Matlab)

用于指纹识别中，对指纹图象的预处理，包括分割、二值化、细化等。(for fingerprint identification, the fingerprint image preprocessing, including segmentation, two values, such as thinning.)

实现椭圆几何畸变矫正，将原始椭圆形变的图像，矫正为矩形正常图像(The correction of elliptical geometric distortion is achieved, and the original elliptical image is corrected to rectangle normal image.)

经典数字水印算法，包括GUI实现 可直接运行(classic digital watermarking algorithm, including the realization of GUI can run)

rgb to HSV，很有用，调试成功，可以应用(rgb to HSV，#include "stdafx.h" #include <iostream.h> void main(float R, float G, float B, float& H, float& S, float&V) { // r,g,b values are from 0 to 1 // h = [0,360], s = [0,1], v = [0,1] // if s == 0, then h =-1 (undefined) float min, max, delta,tmp tmp = R>G?G:R min = tmp>B?B:tmp tmp = R>G?R:G max = tmp>B?tmp:B V = max // v delta = max- min if( max != 0 ) S = delta/max // s else { // r = g = b = 0 // s = 0, v is undefined S = 0 H = 0 return } if (delta == 0){ H = 0 return } else if(R == max){ if (G >= B) H = (G- B)/delta // between yellow & magenta else H = (G- B)/delta+ 6 } else if( G == max ) H = 2+ ( B- R )/delta // between cyan & yellow else if (B == ma)

用于图像的纹理分割，适合用于图像的纹理分割和图像特征分类，并且是基于MATLAB实现的纹理特征分割。(For image texture segmentation, texture suitable for image segmentation and image feature classification, and is based on the MATLAB implementation of the texture features segmentation.)

说明：  使用gpu、cpu并行进行sift算子计算匹配，能够在原来的基础上加速处理，但对显卡要求较高，具体环境配置使用方法可以参照mannual(SiftGPU is an implementation of SIFT [1] for GPU. SiftGPU processes pixels parallely to build Gaussian pyramids and detect DoG Keypoints. Based on GPU list generation[3], SiftGPU then uses a GPU/CPU mixed method to efficiently build compact keypoint lists. Finally keypoints are processed parallely to get their orientations and descriptors. SiftGPU is inspired by Andrea Vedaldi s sift++[2] and Sudipta N Sinha et al s GPU-SIFT[4] . Many parameters of sift++ ( for example, number of octaves, number of DOG levels, edge threshold, etc) are also available in SiftGPU. The shader programs are dynamically generated according to the parameters that user specified. SiftGPU also includes a GPU exhaustive/guided sift matcher SiftMatchGPU. It basically multiplies the descriptor matrix on GPU and find closest feature matches on GPU. Both GLSL and CUDA implementations are provided. )