Image-deblurring-

BMP,ICO,JPG等图片格式转换，按照例子可以任意格式转换(BMP, ICO, JPG and other image format conversion, according to examples can be converted to any format.)

【实例介绍】

数据同化框架下基于差分进化的遥感图像融合算法(Data assimilation framework based on differential evolution algorithm for remote sensing image fusion)

说明：  水体提取功能，里面主要实现了多源遥感卫星水体提取，入库，推送等后续代码功能(Water extraction function, which mainly realizes the multi-source remote sensing satellite water extraction, storage, push and other follow-up code functions)

CSS对边缘图像进行特征点提取然后用改进的NCC算法进行匹配(Using CSS in edge to extract image feature point and then using the modified NCC to match)

卷积神经网络（Convolutional Neural Network）是一个专门针对图像识别问题设计的神经网络。它模仿人类识别图像的多层过程：瞳孔摄入像素；大脑皮层某些细胞初步处理，发现形状边缘、方向；抽象判定形状（如圆形、方形）；进一步抽象判定（如判断物体是气球）。(Convolutional neural network is a neural network specially designed for image recognition. It imitates the multi-layer process of human recognition image: pupil ingestion of pixels; some cells in the cerebral cortex preliminary processing to find shape edges and directions; Abstract judgment of shape (such as circles and squares); and further Abstract judgment (such as judging objects are balloons).)

基于双目的深度图获取,根据图像合成深度图左右视点( depth map based on binocular)

srad斑点去噪各向异性扩散滤波器,代码很短，本身该方法就含有不少的偏微分方程，看懂需要仔细研究。(srad, speckle denoising anisotropic diffusion filter)

基于图象小波变换的图象编码的经典算法．程序中包括压缩和解压缩的过程，有可执行的示例．(Image-Based Wavelet Transform Image Coding Algorithm classic. Procedures, including compression and decompression process, the sample has executable.)

说明：  当前论文主要考虑的是非信号依赖的高斯噪声下的图像恢复，本程序实现了泊松噪声下的图像恢复，泊松噪声为信号依赖噪声，能够更加有效逼近实际成像系统噪声。( This is the code that was used in the papers "A Nonnnegatively Constrained Convex Programming Method for Image Reconstruction", "Total Variation-Penalized Poisson Likelihood Estimation for Ill-Posed Problems", "Tikhonov Regularized Poisson Likelihood Estimation: Theoretical Justification and a Computational Method", "An Efficient Computational Method for Total Variation with Poisson Negative-Log Likelihood", "An Analysis of Regularization by Diffusion for Ill-Posed Poisson Likelihood Estimation," "An Iterative Method for Edge-Preserving MAP Estimation when Data-Noise is Poisson", and finally, "Regularization Parameter Selection Methods for Ill-Posed Poisson Maximum Likelihood Estimation". See my publications page for more details. The main algorithm is for nonnegatively constrained, regularized Poisson likelihood estimation. At this point you can choose Tikhonov, total variation regularization, and diffusion regularization. A number of other methods are also implemented. Regularizatio)