Imageprocessing

说明：  两种基于非下采样变换图像去噪方法，效果比contourlet变换要好(Two transform based image denoising nonsubsampled method, the effect is better than contourlet transform)

基于小波多尺度算法的图像处理边缘检测 matlab(Algorithm based on wavelet multiscale edge detection image processing matlab)

主要完成图像特征出提取，包括5个特征选择算法：SFS，SBS，SFBS(Description The DEMO includes 5 feature selection algorithms: Sequential Forward Selection (SFS) Sequential Floating Forward Selection (SFFS) Sequential Backward Selection (SBS) Sequential Floating Backward Selection (SFBS) ReliefF)

k均值用于图像分割，对于相同颜色但深度不一样可以分割。(k-means for image segmentation, the same color depth can be split.)

点目标质量评估，一维积分旁瓣比、峰值旁瓣比(ISLR PSLR)

运动目标的给总与识别，可以实时显示目标的运动轨迹，支持高速相机实时处理视频数据，并可以获得运动目标的轮廓矩等信息(Moving target to the total and the identification of moving targets in real-time display track, real-time processing to support high-speed video camera and moving target access to information such as contour moments)

基于NSCT变换的自适应去噪，里面包含仿真图(image denoising)

说明：  1.学习使用fft2,ifft2,fftshift,ifftshift函数。用fft2函数对”lena.bmp”做二维傅立叶变换，并显示其频谱，用fftshift函数将频谱坐标原点移动到图像中心。用ifft2函数做傅立叶反变换。（提示：显示频谱时，可以先对频谱取对数，这样可以压缩动态范围很大的频谱，获得更好的显示效果）(1. Learn to use fft2, ifft2, fftshift, ifftshift functions. With the FFT 2 function, the lena.bmp'The two-dimensional Fourier transform is performed and the spectrum is displayed. The origin of the spectrum coordinate is moved to the center of the image by using the FFT shift function. The inverse Fourier transform is done with ifft2 function. (Note: when displaying the spectrum, the logarithm of the spectrum can be taken first, so that the spectrum with a large dynamic range can be compressed to obtain better display effect.))

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：  可以读取输出浮点型、整型、复数型影像，对于遥感专业的所有影像读入输出MATLAB中有很大帮助。采用振幅离差阈值提取PS点(Can read floating-point, integer, and complex type of image, for all remote sensing professional images into the MATLAB will be very helpful)