SUN-saliency

本方法的种子点选取采用Harris角点法，阈值则通过云模型获得，对lena图像进行了较好的分割(The method selected seed points using Harris corner point method, the threshold is obtained through the cloud model, for better lena image segmentation)

一种新的基于snake模型的水平集图像分割方法：用matlab编程实现，可进行灰度图像的分割，里面有演示实例，便于学习。(A new snake model based on the level set image segmentation methods: using matlab programming implementation, can be gray-scale image segmentation, there are demonstration examples for study.)

mean shift图像分割软件,只能对灰度图像进行处理,如果对彩色图像进行处理,需要转换(mean shift image segmentation software, only for grayscale image processing, if the right color image processing, needs to be converted)

使用CGAL库对人体三维网格分割并且把分割后的网格展开到一个平面上(using cgal to segment a mesh an expend )

有详实的说明，基于C-V模型的图像分割，属于活动轮廓模型，有典型的图片例子，可以直接运行，适合研究生使用。(There are detailed instructions, CV model-based image segmentation, are active contour models, with typical picture examples can be run directly, for graduate students to use.)

针对多聚焦图像融合，本文首先介绍了小波变换融合算法，虽然小波变换方法无冗余，高频分量损失较小，具有较好的融合效果，但存在两个主要缺点：一是移变性，二是融合图像在重构时会受到一些外来因素的影响，所以仍会丢失一些边缘信息，为了克服小波变换法的以上缺点，可以采用基于小波分解和点扩展函数模型PSF相结合的融合方法。该方法首先对不同的图像进行无降2采样的小波分解，以保持与源图像大小相同，然后分别将其各方向、各尺度的高频分量进行叠加，并依此提取其高频分量的特征信息来判定清晰目标或模糊目标，以此来设计融合算法，采用一定的策略将两副源图像进行融合，从而避开了小波的反变换，因此融合后的图像具有比小波变换法更好的融合效果。(multi-focus image fusion, this paper introduces the wavelet transform algorithm, Although the wavelet transform non-redundant, the loss of high-frequency components are smaller, better integration effect, But there are two major drawbacks : First, the shift variability and the second is the integration of image reconstruction will be subject to a number of external factors. Therefore, there would still be some marginal loss of information, in order to overcome the wavelet transform of the above shortcomings, can be used based on wavelet decomposition and the point spread function PSF model combining the fusion method. The first pair of different images ratchet two sampling wavelet decomposition, and to maintain the same source image size. Then all of its direction, the scale of high-freque)

说明：  用奇异值分解（SVD）的方法进行噪声去除( noise removing by SVD analysis)

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.)

de-speckling of noise in medical ultra sound images...

基于MATLAB GUI的图像处理界面，包括基本的图像处理功能(Graphical interface construction based on image processing)