颜色直方图

类似于photoshop软件处理，功能复杂简单耐用，适合于初学者学习参考(Similar to the photoshop software processing, functional complexity of simple and durable, suitable for beginners to learn information)

Computer Vision:Algorithms and Applications，Richard Szeliski，适合图像处理人群(Computer Vision: Algorithms and Applications, Richard Szeliski, suitable for image processing crowd)

将RF信号处理为B型图像的工具包,非常好用(a toolkit to transfer RF signal to B-mode images)

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.)

根据CVPR最佳论文实现的基于暗通道的图像去雾算法（含soft matting），以及算法改进：包括对色彩失真的改进以及一种达到soft matting效果的快速算法(According CVPR Best Paper realized based on dark channel images to fog algorithms (including soft matting), and algorithm improvements: Improvements include color distortion as well as a way to achieve fast algorithm for soft matting effect)

针对6自由度运动平台开发的逆解解算、雅克比解算、速度和力解算的程序(6-DOF Motion Platform for Development of Inverse Kinematics solver, Jacobian solver, solver speed and power of the procedure)

使用matlab搭建神经网络，从单目图像中估计深度值(Using matlab to build a neural network to estimate depth from monocular images)

说明：  Forstner算子提取特征点 Forstner算子 提取特征点 (Forstner operator extracting feature points Forstner operator extracting feature points)

本源码是基于Markov chain Monte Carlo (MCMC)的Bayesian inference工具包,其中包括MCMC采样，基于MCMC的高斯分类，同时描述了采样的一些方法。其中还有使用文档(toolbox is a collection of Matlab functions for Bayesian inference with Markov chain Monte Carlo (MCMC) methods)

实现对图像平滑模糊，有简单平滑、高斯模糊和中值滤波三种可选，基于OPenCV类库实现，代码可直接运行(Achieve a smooth blur the image, a simple smooth, Gaussian blur and median filtering three options, OPenCV-based library, the code can be run directly)