image-segmentation-program

本代码主要给出了激光粒度仪颗粒散射光强分布以及4种粒度反演算法，以及4种算法之间的比较。四种反演算法为：TSVD、Chaine、Tikhonov和l1正则化。(The code gives the Zetasizer particle scattering intensity distribution, and four kinds of particle inversion algorithm, as well as a comparison between the four algorithms. Four kinds of inversion algorithm is: TSVD, Chaine, Tikhonov and l1 regularization.)

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. )

1、对观测数据进行中心化，； 2、使它的均值为0，对数据进行白化—>Z； 3、选择需要估计的分量的个数m，设置迭代次数p<-1 4、选择一个初始权矢量（随机的W，使其维数为Z的行向量个数）； 5、利用迭代W(i,p)=mean(z(i,:).*(tanh((temp) *z)))-(mean(1-(tanh((temp)) *z).^2)).*temp(i,1)来学习W （这个公式是用来逼近负熵的） 6、用对称正交法处理下W 7、归一化W(:,p)=W(:,p)/norm(W(:,p)) 8、若W不收敛，返回第5步 9、令p=p+1，若p小于等于m,返回第4步 剩下的应该都能看懂了 基本就是基于负熵最大的快速独立分量分析算法(1, on the center of the observation data, 2, making a mean of 0, the data to whitening-> Z 3, select the number of components to be estimated m, setting the number of iterations p < -1 4, select an initial weight vector (random W, so that the Z dimension of the row vectors of numbers) 5, the use of iteration W (i, p) = mean (z (i, :).* (tanh ((temp) ' * z)))- (mean (1- (tanh ((temp)) ' * z). ^ 2)).* temp (i, 1) to learn W (This formula is used to approximate the negative entropy) 6 with symmetric orthogonal treatments W 7, normalized W (:, p) = W (:, p)/norm (W (:, p)) 8, if W does not converge, return to step 5 9 , so that p = p+1, if p less than or equal m, return to step 4 should be able to read the rest of the basic is based on negative entropy of the largest fast independent component analysis algorithm)

图像交互是分割 graph cut,实现交互式分割，并且可以连续分割(Interactive image is split graph cut, to achieve interactive segmentation, and can be continuously split)

说明：  对加载的图像进行灰度处理，简单处理matlab程序，效果不错，利于后面对图形进一步加工处理(Gray-scale processing of loaded images)

CHEMKIN-III package. Gas mixture sensitivity analysys.

gongzhenQ.m:计算双稳态随机共振系统输入输出信信噪比增益，非常明显的随机共振现象。，已通过测试。 (gongzhenQ.m: calculation of the stochastic resonance of bistable stochastic resonance system input output signal SNR gain, it is clear. , Has been tested.)

基于DCT域的数字水印算法主要包括水印调制、水印嵌入和水印提取，首先在嵌入载体图像之前用Logistic混沌序列对水印进行调制，得到一个只有+1和-1随机序列的水印，同时将载体图像进行全局DCT变换，然后将水印图像嵌入人类视觉系统最重要的部分，即DCT最大的系数，DC（Direct Current）部分也包含在这最大的系数中，这部分的系数满足人类视觉特性，会使水印嵌入的性能更好。嵌入算法是将水印与这些系数进行相乘获得新的系数，再用新的系数来替换原来的系数，即获得嵌入水印后的离散余弦域的图像，然后对这个变换后的图像进行IDCT，就会得到需要的水印图像。(While the carrier image digital watermarking algorithm based on DCT domain include watermark modulation, watermark embedding and watermark extraction, the first of the watermark embedded in a carrier modulated image before using Logistic chaotic sequence, only+1 and-1 to get a random sequence of watermark, Global DCT transform, then the watermark image is embedded most important part of the human visual system, i.e. the largest DCT coefficients, DC (Direct Current) in this section also contains the largest coefficient, the coefficient of this part of the human visual characteristics to meet, make watermarks Embed better performance. The watermark embedding algorithm is with these coefficients are multiplied to obtain new coefficients, and then a new factor to replace the original coefficients, namely discrete cosine domain to obtain an image watermarked and then transformed the image of this conduct IDCT, on watermark image will be needed.)

Roberts算子，Prewitt算子，Sobel算子，Marr算子，Canny算子之一对输入图像 实现边缘检测，输出边缘图像并与matlab自带函数实现进行对比(Roberts operator, Prewitt operator, Sobel operator, Marr operator, Canny operator to achieve one of the input image edge detection, the output edge image and bring their own matlab function compared)

源码PonyProg2000-2 07a tar gz()