Circle-detection

背景差分法运动目标检测，建立背景模型，然后使用当前模型与背景模型相减，再和阈值相比较，比阈值大的即判断为有运动目标，比阈值小的即判断为没有运动目标，阈值大小可以自己适当调试，根据经验值设置最佳阈值。(Background difference method is used for moving target detection and setting up background model, then using current model and background model subtracting, and comparing with threshold, it is judged to have moving target compared with the threshold value, which is smaller than threshold. The size of threshold can be adjusted properly, and the best threshold is set according to experience value.)

说明：  我是一个图象处理的初学者,用MATLAB语言编写了一些内部的函数,实现了图象处理的功能,比如entropy,laplician,otsu,top-hat等(image processing is a beginners MATLAB language some internal functions, achieving image processing functions, such as entropy, laplician, Otsu, top-hat, etc.)

说明：  《数字图像处理（第三版）》课后习题答案，作者冈萨雷斯(Answers to Exercises after Class of Digital Image Processing (Third Edition),author Gonzalez)

高斯粗糙表面的散射系数，输入参数含波长，需要regeng.m产生高斯粗糙表面。(rs1dg computes the bistatic scattering coefficient for Gaussian rough surfaces with Gaussian spectrum.)

改进后的非线性各向异性扩散用于图像中的保边去噪，增加了二阶导数，是滤波效果更好(Improved nonlinear anisotropic diffusion for edge preserving image denoising, an increase of second derivative, is a better filtering effect)

说明：  利用红黑小波进行图像去噪，图像复原，并与常规的小波进行比较(use red, black and wavelet denoising images, image recovery, and with the conventional comparison of wavelet)

介绍基于彩色不变理论的SIFT算法（CSIFT算法）的文章，文章是英文的(Color change based on the theory introduced SIFT algorithm (CSIFT algorithm) article, the article is in English)

本文主要介绍遗传算法的基本理论，叙述遗传算法在图像增强的的主要应用，即将原始图像变得更加清晰，特征变得更加明显。 现今关于图像增强的算法有很多，而这些算法大多是基于退化函数或者点扩展函数的知识进行图像处理的。当图像出现模糊或噪声影响大时，设计出的图像清晰化的效果肯定不够理想，因此有必要对图像进行增强处理。于是，可利用到遗传算法这种成熟稳定的仿生物进化的全局寻优算法，进行图像增强，由于遗传算法控制参数少、自适应度高，将选择该方法对图像退化分别进行不同的清晰化处理. 这样既增强了图像的对比度,又克服了传统直方图均衡化处理所造成的灰度级损失等缺点。 通过实验去表明，遗传算法从全局寻优的角度出发，能够较为精确地估计退化系统函数。和传统的线性增强、直方图均衡进行比较。实验结果表明该方法能改善原图像视觉效果，便于之后的图像分析。 (This paper mainly introduces the basic theory of genetic algorithm, genetic algorithm (ga) in the main application of image enhancement, the original image is more clear, characteristic becomes more obvious. Today about the image enhancement algorithm are many, and most of these algorithms is based on the degradation function or the knowledge of the point spread function of image processing. When the image appears fuzzy or noise influence, designed the image clarity of effect must not ideal, therefore it is necessary to enhance the image. Then, genetic algorithm is available to the mature and stable evolution of the global optimization algorithm, for image enhancement, due to less genetic algorithm control parameters, since the high fitness, will choose the method of image degradation, respectively, to manipulate the different motivation. It can enhance the image contrast, and overcome the traditional histogram equalization processing grayscale loss caused by the faults. Throug)

利用遗传算法进行图像分割的源程序.基于matlab平台,适合于一维和二维分割.(using genetic algorithms for image segmentation of the source. Matlab-based platform, in a fit- and two-dimensional segmentation.)

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)