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Retinex理论的基础理论是物体的颜色是由物体对长波（红色）、中波（绿色）、短波（蓝色）光线的反射能力来决定的，而不是由反射光强度的绝对值来决定的，物体的色彩不受光照非均匀性的影响，具有一致性，即retinex是以色感一致性（颜色恒常性）为基础的。不同于传统的线性、非线性的只能增强图像某一类特征的方法，Retinex可以在动态范围压缩、边缘增强和颜色恒常三个方面打到平衡，因此可以对各种不同类型的图像进行自适应的增强。(The basic theory of Retinex theory is the color of the object by object for the long wavelength (red), medium (green), short wave (blue) light reflection ability to decide, rather than by the intensity of reflected light of the absolute value to decide, the color of the object under illumination nonuniformity effects, consistent with the Retinex, that is based on color constancy (color constancy based). Different from the traditional linear, nonlinear image enhancement method of only one kind of features, Retinex can be in dynamic range compression, edge enhancement and three aspects of color constancy hit the balance, thus enhancing adaptive to a variety of different types of images can be.)

改进的 SUSAN 算法，用于自适应阈值的边缘检测(improved algorithm for the adaptive thresholding edge detection)

说明：  将已知的灰度图像逆时针旋转60度，矩阵运算，图像旋转(Rotate the known grayscale image 60 degrees counterclockwise, matrix operation, image rotation)

这段代码的功能是实现图像去雾处理，Matlab代码，可以直接运行的(Functionality of the code is to realize image processing demisters Matlab code can be run directly)

snake算法的c源代码,一般snake算法可以用于图像的边缘检测,是一种比较新的方法(snake algorithm c source code, the general snake algorithm can be used to image edge detection, is a relatively new approach)

说明：  光流场经典算法-LK算法，通过两幅图像计算光流场。(Lucas – Kanade Motion Estimation using Pyramids)

NRZ type differential phase modulation signal modeling and simulation analysis, Genetic algorithm based reactive power optimization, Matlab for beginner students will help.

利用ENVI/IDL，计算多幅图像的各个像元的平均值。并忽略空缺值(Use ENVI/IDL, calculate the average of each pixel of multiple images. And ignores the value of vacancies)

Fast_and_Robust_Multi-Frame_Super-Resolution这篇文章的算法实现。内含BTV算法和改进的btv算法实现超分辨率重建。(This article Fast_and_Robust_Multi-Frame_Super-Resolution algorithm. Containing BTV algorithm and improved the btv algorithm to achieve super-resolution reconstruction.)

该算法先通过七点进行M估计，然后挑选三点进行精确匹配运算(This algorithm firstly the fuzzy matching to achieve slightly at the beginning of localization, to achieve accurate positioning on the basis of improve the accuracy simulation)