匹配滤波器图像识别

说明：  应用gibbs随机场进行图像分割。效果较好。希望对大家有所帮助。(use gibbs image segment.wish it will help everyone.)

功能：应用Rudin-Osher-Fatemi模型进行图像去噪，在ROFtest.m 中输入图像，附带文档ROFscheme内容为此模型的数值分析过程，比较详细，适合初学者(Classic 􏰉 Rudin-Osher-Fatemi model denoising, the including documentation is the numerical analysis process of the model in detail, suitable for beginners)

通过小波包变换进行工业系统中的故障识别，去噪(Wavelet Transform)

说明：  利用小波变换技术实现，最简洁的图像融合例子(image fusion.The simplest example of image fusion using wavelet transform technology.)

可对灰度及彩色图像进行压缩及解压缩，通过变量名可以实现基于不同方式（多级树集合分裂spiht，ezw,stw,wdr等）的压缩，形如wcompress( c ,X,SAV_FILENAME,COMP_METHOD)(The wcompress command performs either compression or uncompression of grayscale or truecolor images.)

(l)小波分析理论在变形监测数据处理研究中的理论意义和实用价值 (2)小波阂值去噪和多分辨分析在变形监测信号分析中的应用 (3)在算法和图像处理方面的优越性 ((L) wavelet analysis theory in the study of deformation monitoring data processing theoretical significance and practical value (2) wavelet thresholding denoising and multi-resolution analysis in deformation monitoring signal analysis application (3) in the algorithm and image processing superiority )

一种基于CDD的图像修复算法，效果还不错，做图像修复的可以好好看看，还有论文哦 (Based CDD image restoration algorithm, the results were pretty good, do image restoration can be a good look, there are papers Oh)

高光谱分析工具包 用于matlab环境中 可以比较省事实力的对高光普图像分析 很实用(hyperspectral analysis)

　对经典的二值化方法Ostu 算法和Bernsen 算法中存在的缺点进行了分析, 提出一种结合Canny 算子的图像 二值化方法.该方法综合考虑了边缘信息和灰度信息, 通过边缘附近种子点在高阈值二值化图像中的填充和低阈值 图像对它的修补而得到二值化结果图像, 较好地解决了经典二值化方法中存在的抗噪能力差、边缘粗糙、伪影现象 等缺点.实验结果证明, 该方法能够较好地解决低对比度图像和目标像素灰度不均匀图像的二值化问题(The disadvantage of the classical binary method Ostu Bernsen algorithm and algorithms exist were analyzed, one binding Canny operator image binarization method. This method considers the edge information and gray information, through seed near the edge point padding and a low threshold image to its repair in a high threshold binary image to obtain a binary result image, it solves the noise immunity classical binary method exists difference, rough edges, artifacts phenomenon and other shortcomings. the experimental results show that this method can solve the low-contrast image and the target image pixel gray uneven binary problem)

楔波变换，在SAR图像中实现边缘检测，为目标识别做铺垫工作。(The wedge waves transform, SAR image edge detection, target identification pave the way for the work.)