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关于计算机视觉和图像的matlab工具箱。包括相位一致性特征，空间特征检测，积分图像，非极大值抑制和滞后阈值，边链接和线段拟合，去噪，等(MATLAB and Octave Functions for Computer Vision and Image Processing。such as • Feature Detection via Phase Congruency • Spatial Feature Detection • Integral Images • Non-Maxima Suppression and Hysteresis Thresholding • Edge Linking and Line Segment Fitting • Test Grating for Edge Detection • Image Denoising • Surface Normals to Surfaces • Scalogram Calculation • Anisotropic diffusion • Grey Scale Transformation and Enhancement • Frequency Domain Transformations • Functions Supporting Projective Geometry • Feature Matching • Model Fitting and Robust Estimation • Fingerprint Enhancement • Interesting Synthetic Images • ASCII Image Generation • Rotation Transforms • Image Blending • Colourmaps and colour conversions • Image Display, Image Writing and Miscellaneous )

沙威关于压缩感知（包括多种重构算法）和小波变换的程序(compressive sensing and Wavelet and source code)

LDA 的matlab源码实现，Jonathan Huang编写的，是目前唯一可用于且正确的源码，可用于图像特征降维(LDA to achieve the matlab source, Jonathan Huang, prepared, is the only can be used and the correct source, can be used for image feature dimensionality reduction)

利用压缩感知实现波达方向估计，运用奇异值分解对接收信号进行降维，再利用L1范数进行估计(Using compressed sensing DOA estimation using singular value decomposition to reduce the dimensionality of the received signal, and then using the L1 norm estimate)

一种鲁棒性较强的提高图像阴影区域质量的图像增强技术，LITAO(A Robust Image Enhancement Technique for Improving Image Visual Quality in Shadowed Scenes)

用matlab编写的进行椭圆检测的算法，用到Hough变换(Using matlab for ellipse detection algorithm, Hough transform is used)

graphcut 图像分割经典论文 英文版(graphcut image segmentation classic paper in English)

说明：  基于稀疏表达的多源图像数据融合，遥感图像融合(Multi-source image data fusion based on sparse expression, remote sensing image fusion)

用主成分分析来降维，用Kmeans方法聚类；应用于变化检测中(Principal component analysis is used to reduce dimension with k-means algorithm is used to cluster; change detection)

一个散焦模糊自动复原的算法，自动估计散焦半径，在频率域识别参数，并用最小二乘滤波复原(A defocus blur automatic recovery algorithm automatically estimated defocus radius, in the frequency domain identification parameters, and by the least squares filter restoration )