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matlab code for image fusion based on curvelet transform and genetic algorithm

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.)

利用非线性结构张量处理一些图形问题，能够有效的解决和优化现成的处理方法(In this article, we introduce nonlinear versions of the popular structure tensor, also known as second moment matrix. These nonlinear structure tensors replace the Gaussian smoothing of the classical structure tensor by discontinuity-preserving nonlinear diffusions)

用傅立叶变换的方法在频率域实现图像处理，并比较从幅度和相位恢复图像的区别，已经通过调试(Fourier transform method used in the frequency domain realization of image processing, and compare the amplitude and phase from the difference between the restoration of images, has passed debugging)

对SWAN输出文件进行数据处理及图像输出(SWAN output file, data processing and image output)

颜色特征提取，提取空间为HSV颜色空间，颜色特征提取，提取空间为HSV颜色空间(color extraction)

完整的可运行AAM模型的matlab代码，附有测试图像，matlab 2009测试通过(Complete AAM model can run matlab code, with a test image, matlab 2009 test pass)

一种基于背景减法和帧差的运动目标检测算法(Based on background subtraction and frame difference moving target detection algorithm)

运动目标检测与跟踪，包括目标定位，匹配与跟踪!(moving target detection and tracking, including Target, matching and tracking!)

为了提高数字图像中椭圆检测的效率和准确性,提出了一个基于最小二乘法的改进的随机椭圆检测算法. 该算法随机选取图像中的3 个边缘点,在以这3 个点为中心的窗口内,从边缘点中拟合出可能椭圆,并通过随机选 取的第4 个边缘点来确认可能椭圆. 利用直接最小二乘法椭圆拟合的特性,引入可能椭圆边缘点收集和椭圆重新 拟合的迭代过程来提取最终的椭圆参数. 通过对含有不同噪声的仿真图片和包括残缺椭圆的实际图片的实验表 明,新算法的改进是有效的. 与原算法相比,新算法降低了对参数的依赖性,提高了检测的速度、稳定性和准确性, 同时保留了原算法的抗噪声能力.(: An imp roved randomized ellip se detection algorit hm based on least square approach was proposed to enhance t he efficiency and accuracy of ellip se detection in digital images. This algorit hm randomly se2 lect s three edge point s in t he image , and t hen uses least square approach to fit all t he edge point s in three windows , which are defined by t he t hree edge point s. The forth edge point is randomly selected to judge whet her a possible ellip se exist s in t he image. Utilizing the characteristic of direct least square fit ting of ellip se , an iteration process of edge point collecting and ellip se refit ting of possible ellip se was int roduced to ext ract t he final ellip se’s parameters. Artificial images wit h different level s of noise and nature images containing incomplete ellip ses were employed to test t his algorithm. Experimental result s show that t he improvement s are notable. Compared with the original algorit hm , t he propo sed algorit hm reduces)