jpegyasuo

实现图像的二阶巴特沃斯(Butterworth)低通、高通滤波器，高斯低通、高通滤波器(Butterworth LPF、Butterworth HPF、Gaussian LPF、Gaussian HPF)

令x(n)=5exp(j*0.15*n*n)+6exp(j*300n-j*0.15*n*n) ，w(n)为高斯窗函数。试用matlab软件，取不同长度的窗函数，分别求x(n)离散短时傅里叶变换，并进行信号重构。(ORDER x (n) = 5exp (j* 0.15* n* n)+6exp (j* 300n-j* 0.15* n* n), w (n) for the Gaussian window function. Trial Matlab software, take different lengths of the window function x (n), respectively, seek to discrete short-time Fourier transform, and to reconstruct the signal.)

鼠标移动到哪里 就显示那里的颜色像素值

说明：  基于开源计算机视觉库OpenCV的图像处理基于开源计算机视觉库OpenCV的图像处理(Based on open source computer vision library OpenCV image processing based on open source computer vision library OpenCV image processing)

说明：  利用已知的平坦道路的视差图，得出uv方向的直方图，并且求出直线(The histogram of the UV direction and the straight line are obtained by using the disparity map of the known flat road.)

说明：  这是一个比较实用的ADBOOST算法的源代码，它是比较准确，希望大家喜欢。(This is a more practical algorithm ADBOOST source code, it is more accurate, I hope you like.)

说明：  图像处理，运动放大，视频代码展示，以及输出结果(steerable pyramid algorithm)

该代码是基于学习的超分辨率重建，此算法是在线字典学习，字典的训练与稀疏表示与重建同时进行。(This code is based on the study of super-resolution reconstruction, this algorithm is learning online dictionaries, dictionaries of training and sparse representation and reconstruction simultaneously.)

模式识别中运用ICA进行特征提取的matlab代码(Pattern Recognition in the use of ICA for feature extraction matlab code)

图像修复是对图像中破损区域进行信息填充，以减少图像破损所带来的信息损失的过程。 传统的图像修复方法需要依赖图像的具体结构来制定相应的修复方法，压缩感知理论的提出，使得可以利 用信号的稀疏性来对图像进行修复。基于K 奇异值分解（KSVD）与形态学成分分析（MCA，Morphological Component Analysis）的图像修复方法首先采用形态学成分分析方法对破损图像进行特征分析，将其分解 为结构部分和纹理部分；然后基于学习型字典KSVD分别对这两部分进行过完备字典训练；最后利用训练得 到的字典实现对破损图像的修复。相比于传统的图像修复方法，该方法具有适应性强、修复效果好等优点(Image inpainting is to fill the missing data in corrupted images and thus to reduce the information loss of damaged image. Traditional inpainting algorithms are dependent on specific structure of target images compressive sensing theory makes is possible to realized image inpainting with signal sparsity. This paper proposes a novel inpainting algorithm based on KSVD and MCA algorithm, which first decomposes the image into texture part and structure part, and then trains the two dictionaries for these two parts with KSVD and reconstructs the original image with these two trained dictionaries. Experiment indicates that the proposed algorithm is of better adaptability and performance as compared with traditional algorithms.)