Log_gabor

运用harr特征+SRC（稀疏表示）分类实现的一种车辆检测方法，文件中提供了训练和测试车辆图片。由于时间原因，所用haar特征没有优化，维度过高，导致滑窗框图过慢，本代码只输出效果统计数据，以供大家参考学习稀疏表示在车辆检测中的应用。(Using harr feature+SRC (sparse representation) classification to achieve a vehicle detection method, the paper provides a training and test vehicle picture. Due to time reasons, the use of haar feature is not optimized, high dimension, resulting in sliding sash figure is too slow, the effect of the code only output statistics for your reference learning sparse representation in the vehicle detection.)

说明：  一种gamma校正的matlab的源代码(A gamma correction of the source code matlab)

说明：  用于立体匹配的三种算法，显示视差图，matlab代码(Three algorithms for stereo matching, display parallax map, matlab code)

模糊集图像增强：设计隶属度函数将图像从空间域变换到模糊集域；设计模糊增强算子，在模糊集域对图像进行处理；根据隶属度函数重新将图像从模糊集域变换到空间域。(Fuzzy image enhancement: Designing the membership function of the image from the spatial domain to the fuzzy set domain design fuzzy enhancement operator in fuzzy set domain for image processing membership function according to re-image from the fuzzy set domain to the spatial domain .)

针对杂波环境下的多个机动目标跟踪问题, 本文将多模型概率假设密度 (Multiple-model probability hypothesis density, MM-PHD) 滤波器和平滑算法相结合, 提出了 MM-PHD 前向 – 后向平滑器. 为了避免引入复杂的随机有限集 (Random finite set, RFS) 理论, 本文根据 PHD 的物理空间 (Physical space) 描述法推导得到了 MM-PHD 平滑器的后向更 新公式. 由于 MM-PHD 前向–后向平滑器的递推公式中包含有多个积分(By integrating the multiple-model probability hypothesis density (MM-PHD) filter with the smoothing al- gorithms, an MM-PHD forward-backward smoother is proposed in this paper for tracking multiple maneuvering targets in clutter. To avoid use of complex random finite set (RFS) theory, the backward updated equation of the MM-PHD smoother can be derived according to the physical-space explanation of the PHD)

使用大津法选定二值化阈值，并对彩色图像做二值化处理(Otsu binarization threshold is selected, and the color images do binarization processing)

视频格式转换 这里主要是mpeg格式 转化为avi，yuv等多种格式(Video format conversion here is mainly converted to avi mpeg format)

Tae Hoon Kim教授的Nonparametric Higher-Order Learning for Interactive Segmentation源码(Tae Hoon Kim, Professor Nonparametric Higher-Order Learning for Interactive Segmentation)

本文首先概述了独立成分分析与盲信号分离， 主成分分析的关系， 然后系统地介绍了该技术的基本概念和数据模型， 对现今比较流行的各种独立成分分析算法进行了剖析和总结。最后对独立成分分析的发展及应用前景作了展望(In this paper, an overview of independent component analysis and blind signal separation, principal component analysis of the relationship, and then systematically introduces the basic concept of the technology and data models for today' s more popular variety of independent component analysis algorithm is analyzed and summarized. Finally, independent component analysis of the development and application prospects are described)

LK光流算法，包括opencv中LK稀疏跟踪的原理，主要是几篇英文文献，另外还有LK的matlab代码(LK optical flow algorithms, including LK sparse tracking opencv in principle, mainly a few in English literature, in addition to LK matlab code)