ImgHazeRemoval_Test

该算法可以应用于计算机视觉的物体识别以及3D重构中。(The algorithm can be applied to object recognition in computer vision and 3D Reconstruction.)

说明：  锐化图片 拉普拉斯算法 两种方法 一种是自己写的一种是用了matlab里面自带的函数(ruihua picture Laplace there are two mechof a fi [as fs aflasl;nvb)

多媒体图形图像正交变换语言是VC++,源码正交变换(Multimedia graphic image orthogonal transform language is VC++ source orthogonal transformation)

实现原始的JPEG图片编解码，不借助任何的第三方库，纯C++。(To achieve the original JPEG image decoding, without using any third-party libraries, pure C++.)

箔条干扰的特性与雷达抗箔条技术研究，对雷达制导导引头的干扰技术进行系统研究(Characteristics of the anti-radar chaff and chaff research technology, the interference radar guidance seeker system research)

一个功能比较全面的图像处理系统，对初学者很有参考价值。(One features a more comprehensive image processing system, useful for beginners reference value.)

主要用于打开8位、24位BMP图像，并对其进行相应的处理，如：颜色分量提取，检测等(key to open the eight, 24 BMP images, and its corresponding treatment, such as : color component extraction, testing)

混合高斯(Mixture of Gaussian, MOG) 背景建模算法和Codebook 背景建模算法被广泛应用于监控视频的运动目标检测问题, 但混合高斯的球体模型通常假设RGB 三个分量是独立的, Codebook 的圆柱体模型假设背景像素值在圆柱体内均匀分布且背景亮度值变化方向指向坐标原点, 这些假设使得模型对背景的描述能力下降. 本文提出了一种椭球体背景模型, 该模型克服了混合高斯球体模型和Codebook 圆柱体模型假设的局限性, 同时利用主成分分析(Principal components analysis, PCA) 方法来刻画椭球体背景模型, 提出了一种基于主成分分析的Codebook 背景建模算法. 实验表明, 本文算法不仅能够更准确地描述背景像素值在RGB 空间中的分布特征, 而且具有良好的鲁棒性.(The background modeling algorithm of mixture of Gaussian (MOG) and codebook is widely used in moving object detection of surveillance video. However, the ball model of MOG usually assumes that the three components of RGB are independent, while the cylinder model of codebook assumes that the value of background pixel is distributed uniformly within the cylinder and the changing direction of brightness points to the origin of the coordinate system. These assumptions reduce the descriptive capability for background modeling. Therefore, the paper proposes an ellipsoid- based background model, which overcomes the MOG and codebook0s limitations. By using principal component analysis to depict the ellipsoid background model, a novel PCA-based codebook background modeling algorithm is proposed. Experiments show that this algorithm can not only give more accurate description of the distribution of background pixels but also have a better robustness.)

说明：  Perona和Malik在热传导方程的基础上，建立了各向异性扩散方程并将其应用到了图像处理中尺度空间的图像平滑上，该模型针对图像的边缘部分和非边缘部分进行不同性质的图像处理，同时解算方程的迭代格式简单，克服传统滤波的主要缺陷，是图像质量大为改善，为图像的边缘检测和增强开辟了新的方向。(This process smoothes regions while preserving, and enhancing, the contrast at sharp intensity gradients.)

图像的逆滤波 维纳滤波 同时可以对图像进行模糊处理比如运动模糊 卷积模糊(Using C++ to complete images of conversion, processing and compression process, is to learn good reference digital image processing program!)