matlab图像稀疏表示代码

实现了C聚类以后的马尔科夫图像分割，对阈值的选取和图像的后验概率计算(C clustering after the Markov segmentation, the posterior probability threshold value is selected and images calculated)

digital image processing project TUMOR DETECTION

通过对于CT图像的读取来进行三维的脑部显示，有助于学习基于matlab的CT图像三维重建过程(Conducive to learning through the reading of CT images to three- dimensional brain display matlab- based CT image 3D reconstruction process )

segmentation using region growing in an image

经过二维混沌序列构成的相位板的双随机相位系统再经过菲涅尔变换后得到的加密解密(Encryption and decryption after Fresnel transformation of the double-random phase system of a phase plate composed of two-dimensional chaotic sequence)

快速运动去模糊，在盲去卷积过程中运用一些加速算法(Fast motion to blur in the blind deconvolution algorithm to accelerate the process of using some)

图像处理中的边缘检测以及曲线拟合的结合应用，实现边缘连接和线段拟合源码(image processing edge detection and curve fitting combination of applications, connectivity and edge line fitting FOSS)

说明：  无下采样的contourlet变换阈值去噪； 无下采样的contourlet变换matlab7.0工具箱(No down-sampling of Contourlet Transform Thresholding Denoising without down-sampling the transform Contourlet matlab7.0 Toolbox)

基于PCNN的特征提取,PCNN用于特征提取时，具体平移、旋转、尺度、扭曲等不变性，这正是许多年来基于内容的图像检索系统追求的目标，同时PCNN用于特征提取时，有很好的抗噪性。而且PCNN直接来自于哺乳动物视觉皮层神经的研究，具有提取图像形状，纹理，边缘的属性。用PCNN能很好地对图像进行签名，将二维的图像的特征提取成一维矢量签名。(Feature extraction of specified object is an important preprocessing stage in machine vision systems. In this paper, we present a novel hybrid feature extraction method using PCNN (Pulse Coupled Neural Network) and shape information. First, we use PCNN firing map train to formulate object’s time signature, then we use roundness of each firing map to formulate object’s shape information vector, the final feature matrix we got is combined time signature and roundness. We take correlations as our judge criteria in our experiments. It has been proved that the algorithm is not sensitivity with the rotation, scaling and translation of the object and is a useful method for target recognition applications.)

说明：  一个用于图像描述表示的脊波变换程序，值得参考。(Used to describe an image expressed by the ridge of wavelet transform process, a good reference.)