matlab实现s小波变换代码,输入图像矩阵，输出一幅图像，分为四块...

数字图象处理教程的ppt格式课件（北理工）-Digital image processing tutorial ppt format Courseware (Northern Polytechnic)

边缘检测与分割源代码 edgedetect.m, houghtr.m, quadtree.m, regrow.m, sobeledge.m, straightline.m, thresh.m, watersd.m 算法包括Prewitt、Roberts、Log、Canny、Sobel算子实现边缘检测，基于Hough变换的直线检测，4叉树区域分割，分水岭分割。（算法对应源文件名）-Edge Detection and Segmentation of the source code edgedetect.m, houghtr.m, quadtree.m, regrow.m, sobeledge.m, straightline.m, thresh.m, watersd.m algorithm includes Prewitt, Roberts, Log, Canny, Sobel Operator realize edge detection, Hough Transform-based line detection, 4-tree region segmentation, watershed segmentation. (Algorithm for the corresponding source file name)

图像降噪 对图像中的加性噪声能够自适应滤除-Image denoising the image of the additive noise can be self-adaptive filtered。

vc图像处理比较全面的程序，提供了图象直方图均衡，robert,sobel,prewitt,kirsch,gauss等方法的边缘检测运算，中值滤波，二维FFT变换和DCT变换，图象的反转，旋转等一些基本的图象模板变换和点变换的功能。目前只处理256*256的图象-vc images deal with more comprehensive procedures, provided the image histogram equalization, robert, sobel, prewitt, kirsch, gauss and other methods of edge detection operator, median filtering, two-dimensional FFT transform and DCT transform, image reversal, rotating images, such as some basic templates and point transform transform function. Currently only deal with 256* 256 image

Dalsa netlink 图像采集设备试验程序。 说明：需要图像采集卡安装后才能够有对应的驱动库。-Dalsa Netlink image acquisition equipment testing procedures. Note : the need for image acquisition card can be installed after corresponding driver library.

用matlab编写的一个程序， 很好啊，大家多下载一下-Using a program written in matlab, well ah, we look more to download

ncut分割算法matlab代码,实现图像分割较好的方法-matlab code ncut segmentation algorithm to achieve better image segmentation methods

本代码用于处理图像增强，主要用VC++语言完成-Image enhancement

用photoshop制作的雕刻效果的详细步骤-Photoshop sculpture produced by the effect of the detailed steps

针对传统方法难以可靠估计图像中纹理单一区域像素点视差的问题,将纹理分析应用于立体匹配中,提 出图像分块整体匹配的方法。首先用LBP/C纹理分析方法对图像纹理进行描述 然后进行基于区域生长的扩张检 测,得到纹理单一图像块 最后对图像块进行整体匹配,得到纹理单一区域的稠密视差图。对国际标准图像进行测试, 结果表明该算法能提高纹理单一区域稠密视差图的精度,具有实用价值 -Due to the difficulty of getting disparity of less textured pixels with traditional approach, block matching algorithm with texture analysis was put forward. First, the images were described by LBP/C texture analysis. Then the expansion detection based on region growing was performed, and the less textured blocks were acquired. Finally the dense disparitymap of less textured area was obtained through block matching. The proposed algorithm was tested with the international standard image data and comparedwith some existing algorithms. The experimental results show that the proposed algorithm can improve the accuracy of disparitywhen handling less textured areas and can be used in practic