fourier

【实例简介】

SVM支持向量机在图像分割中的应用，包含Matlab源代码和SVM所用函数。(SVM support vector machine applications, including image segmentation Matlab source code and functions used by SVM.)

1. 理解彩色图像的颜色分层原理和方法 2. 利用颜色分层方法对彩色图像进行分层处理 3. 实现对身份证标准图像的背景分离和皮肤区域提取(1 understand the color image color layering principles and methods (2) the use of color layered approach for hierarchical processing of color images 3 to achieve the standard of identity and separation of the background image to extract the skin region)

这些代码是有关数字图像处理的一些算法，大家有需要的，可以在里面找些与自己相关的(These codes are some of the digital image processing algorithms, we need, in which you can find some with their associated)

hausdorff距离的一种改进算法，是我自己编写的，用于提取焦点之后的图像配准(hausdorff distance of an improved algorithm, which I have written for the extraction of the focus after the image registration)

实现图像的几何变换，包括图像的平移、镜像变换、缩放、转置以及旋转。(Achieve geometric transformation of image, including the image translation, image transformation, scaling, transpose and rotation.)

图像处理源代码，基于Hough变换的人眼虹膜定位方法，基于Kalman滤波的目标跟踪，基于模糊集的图像增强方法，基于蚁群算法的图像边缘检测。等等(Image processing source code, Hough transform based human eye iris location method, Kalman filter based target tracking, fuzzy set based image enhancement method, ant colony algorithm based image edge detection. and many more)

采用小波变换提取图像特征，对图像特征点进行匹配可以实现畸变图像校正。(Using wavelet transform to extract image features, the image feature points matching can be achieved distortion image correction.)

2基于NSCT的遥感图像融合性能评价及分析.pdf(2 based on remote sensing image fusion performance evaluation and analysis of NSCT. PDF)

图像修复是图像处理的一个重要问题。这是一个困难的问题，同时填写在地区缺少图像信息的纹理和结构。以损坏的图像inpaint失踪的结构和纹理信息，基于小波分解的图像修补算法提出。首先损坏的图像分解成子图像和纹理结构，利用小波子图像转变。然后，地区结构中缺少的信息的子图像重建曲率驱动扩散（CDD），算法，而在同一区域的纹理子图像填写基于改进的纹理合成的典范 最后，恢复的图像，通过重组，结构和纹理恢复的结果。大量的实验表明，该算法可以快速，高效地恢复在同一时间的结构和纹理信息，视觉效果和峰值信噪比比（PSNR）比同类算法更好。(Image inpainting is an important problem image processing. It is a difficult problem to simultaneously fill-in the texture and structure in regions of missing image information. In order to inpaint the damaged image with both missing the structure and texture information, an image inpainting algorithm based on wavelet decomposition is presented. First the damaged image is decomposed into structure sub-image and texture sub-image using the wavelet transformation. Then, the sub-image with the region of missing information in the structure is reconstructed by Curvature-Driven Diffusions (CDD) algorithm, while the same region in the texture sub-image is filled-in with the improved texture synthesis based on exemplar Finally, the restored image is given by recombining the structure and texture restored results. A large number of experiments show that the proposed algorithm can quickly and efficiently restore the structure and texture information at the same time, and the visual eff)