ENVI下温度植被干旱指数(TVDI)

MATLAB实现数字图像处理和函数绘图的学习，不仅可以掌握基本MATLAB的使用，而且是数字图像处理的入门级学习。(The learning of digital image processing and functional drawing by MATLAB can not only grasp the use of basic MATLAB, but also be an entry-level learning of digital image processing.)

这是基于稀疏表示的图像重建，用来做图像去模糊或超分辨，绝对可以用(Sparse Representation for Image Restoration)

本程序集合了互信息配准，PV差值，powell算法，基于小波变换的图像融合的一整套算法。只需要在GUI界面输入两幅图像，即可自动完成图像的配准融合。程序包含Matlab源代码。用Matlab打开imagefusion.m，即会弹出gui界面。融合前要输入参考和浮动图像。图像要求像素的 长＊宽 一样。否则会报错。程序只能处理灰度图像，彩色图像也会转化成灰度图像处理。程序代码已经有详细的注释，方便读者理解。(The procedures set of mutual information, PV difference, powell algorithm, based on wavelet transform image fusion set of algorithms. Only need to enter the two images in the GUI interface, you can automatically complete the image registration fusion. Program contains Matlab source code. Using Matlab open imagefusion.m, gui interface will pop up. Fusion before the input reference and floating images. Image requires the same pixel length* width. Otherwise incorrect. Can only handle grayscale images, color images into gray image processing also. Program code has detailed notes, to facilitate understanding.)

MATLAB程序；图像的小波系数提取，然后进行奇异值分解，得到图像的特征系数。(MATLAB program wavelet coefficients of the image extraction, and singular value decomposition, image feature coefficients.)

图像校正的Matlab代码，非常不错，可以实现很好的校正结果，速度也很快(Image correction of Matlab code, very good, very good correction can be achieved the result of quick)

[1] 鼠标拖动裁剪框可移动裁剪区域的位置 联合开发网 - pudn.com

基于MATLAB的Brovery变换（图像融合）(Image Fusion)

SURF算法作为一种新近出现的特征提取方法，在重复度、独特性、鲁棒性3个方面，均超越或接近以往提出的同类方法，并在计算效率上具有明显的优势。本代码采用SURF算法检测图像并进行坐标变换与图像拼接。 采用SURF算法对图像进行检测，其主要是用Hessian矩阵对图像进行检测，对图像的特征提取之后找到图像的特征点。之后采用最近临快速匹配（NN）、随机抽样一致性（RANSAC）算法和最小二乘法参数优化（LM）对特征点进行提纯匹配。最后在两幅图像中进行坐标变换，达到统一坐标系和图像拼接的效果。 (SURF（Speeded Up Robust Features） as a method of feature extraction which newly appeared is over or nearly previous method on duplication, uniqueness, and robustness and have a clear advantage on computational efficiency. This code uses the SURF and coordinate transformation algorithm to detect image and image matching. This code uses the SURF algorithm of image detection, the main is to use the Hessian matrix of image for testing, to find the image after image feature extraction of feature points. After we used Nearest Neighbor (NN), Random Sample Consensus (RANSAC) algorithm and least square parameter optimization for purification of matching feature points. Coordinate transformation in the last two images, to coordinate system to achieve the same image stitching. )

特征点匹配时，采用构造KD-tree，用最优节点优先法寻找最佳匹配点(Matching feature points, the tectonic KD-tree, with the optimal node is preferred method to search for the optimal matching point)

局部熵差图象匹配并行算法的分析和 功能以及和其他算法的比较(err)