zernike

说明：  BP神经网络做曲线拟合，BP网络应用于曲线二次拟合(BP neural network to do curve fitting, BP network used in curve fitting quadratic)

说明：  文件说明： a1:将二进制文件转为Matalb数据 并批量保存为mat格式 a2:mat数据批量转为图片(RGB三通道） a3:RGB图片批量转灰度图、批量改变图片大小 a4:动图制作 a5:用训练好的网络对图像语义分割(Document description: A1: Convert binary files to Matalb data and save them in batch as mat format A2: mat data batch to picture (RGB three channel) A3:RGB Picture Batch Grayscale, Batch Change Picture Size A4: Motion Mapping A5: Segmentation of image semantics using trained networks)

魔方源代码，用鼠标可以选择想要转动的面，按D顺时针旋转，按 S逆时针旋转。(Cube the source code, you can use the mouse to the face you want to rotate, press D to rotate clockwise, counterclockwise rotation S.)

EMD端点效应参考代码，包含多个算法：极值平均，边界特征尺度延拓，极值延拓，基于ISBM延拓，平行延拓，镜像延拓(EMD end effect reference code contains multiple algorithms: extreme average, the boundary characteristic scale extension, extreme extension, extension based ISBM parallel extension, mirror extension)

compressing the image using JPEG 2000 compression coding to get 10:1 ratio

计算灰度共生矩阵的Matlab程序，提取图像灰度共生矩阵( glcm image segmentation matlab GLCM program segmentation glcm GLCM Matlab Code image segmentation GLCM matrix )

粒子滤波 图像处理程序,内有5个用于图像处理的程序(partical filter)

这是一个地震数据多尺度分析和处理的文章.内容相当丰富,不仅仅增加地质方面的知识,更重要的是可以学到很多数据处理和小波分析方面的知识.(This is a multi-scale seismic data analysis and processing of the article. Fairly rich, is not only increasing geological knowledge, the more important it is to learn a lot of data processing and wavelet analysis knowledge.)

这本教科书，介绍了稀疏和多余的申述，对信号和图像处理应用的重点。的理论和数值基础处理前的应用进行了讨论。信号源的数学建模一起讨论如何使用适当的模型，如去噪，恢复，分离，插值和外推法，压缩，采样，分析和合成，检测，识别，多任务。这次报告会是优雅和迷人的。(Sparse and Redundant Representations From Theory to Applications in Signal and Image Processing )

光场图像渲染技术，利用稀疏分层算法对图像深度进行分层渲染，再利用颜色一致性约束进行去噪处理，通过所给出的图像阵列渲染出中间各个视点的图像(Optical field image rendering technology, the use of sparse hierarchical algorithm for image depth rendering, and then the use of color consistency constraints for noise processing, through the given image array to render the image of the middle of the various views)