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包括harris经典算法、harris-Laplace算法，以及susan算法，鲁棒性好(Harris, including the classic algorithm, harris-Laplace algorithm, as well as susan algorithm, better robustness)

实现人脸识别及分割，使用人脸进行RGB颜色提取，并分层提取特征信息。(Realize face recognition and segmentation, use face for RGB color extraction, and extract feature information hierarchically.)

图片雾化效果 实例

该文件夹包括代码及其对应的论文。其作用在于模拟人类视觉系统的生理特性--视觉注意机制，按照人眼观察外界的方式，检测视觉显著性物体和区域，并阐述了显著性区域的显著性密度和尺度之间的关系，可应用于生物视觉模拟、视觉目标检测、视觉目标跟踪、视觉智能监控，以及视觉生理学和视觉心理学等的研究中。(This document contains codes and the corresponding paper. The aim is to simulate a physiological characteristic of human visual system called visual attention mechanism. The code is used to detect salient objects or regions following the way human eye observes the world. The relation between density and scale of salient object/region is described. It has found widespread use in numerous applications such as biological vision simulation, visual object detection, visual object tracking, visual intelligent surveillance, visual physiological, and visual psychology.)

用DHNN （离散Hopfield网络）存储6幅图像作为联想记忆信息，然后对图像进行加噪处理，用所设计的DHNN进行图像复原，给出结果。(Storing DHNN (discrete Hopfield network) six images as associative memory information, and then add noise to the image processing, image restoration designed with DHNN, shows the results.)

基于相位一致性与K-means方法的结合边缘检测(PC and K-means)

说明：  LBP算法实现图像的纹理分类，基于论文：multiresolution gray scale and rotation invariant texture classification with location binary patterns(LBP algorithm to achieve image texture classification, based on the paper: Multiresolution gray scale and rotation variant texture classification with location binary patterns)

关于图像分割的一个代码，最小生成树Prim算法，能够实现相应功能，拿出来与大家共享(Image Segmentation on a code, Prim minimum spanning tree algorithm, can achieve the corresponding functions, and show to share with you)

合成孔径雷达成像算法仿真程序(Synthetic aperture radar imaging algorithm simulation program)

说明：  给出了一种基于小波分形的图像有损压缩方法.首先，利用小波变换将图像分解为不同频率的分量，然后采用分形迭代函数系统、Huffman树等方法对它们进行编码.实验表明，该算法在保证还原图像质量的情况下，有较高的压缩比.(Image Compression Bassed on Wavelet and Fractal)