palm-recognition

说明：  针对输入180个波束数据，通过使用抛物线插值法进行插值，最终得到720个波束的数据，用于图像显示(For 180 beam data input, 720 beam data are obtained by parabola interpolation method for image display)

用于实现高密度人群聚合检测 包含：边缘检测、灰度共生矩阵计算、SVM特征分量的分类(For achieving high-density population polymerization detector comprises: edge detection, gray level co-occurrence matrix calculation, classification SVM characteristic component)

基于马尔科夫随机场的，例子学习超分辨率复原代码。(This is an implementation of the example-based super-resolution algorithm. Although the applications of MSFs have now extended beyond example-based super resolution and texture synthesis, it is still of great value to revisit this problem, especially to share the source code and examplar images with the research community. We hope that this software package can help to understand Markov random fields for low-level vision, and to create benchmark for super-resolution algorithms.)

基于伽马分布的极化SAR图像CFAR检测算法的研究与实现(gamma distribution CFAR detection)

计算交通格子模型的能量耗散和污染排放，包括 一氧化碳，一氧化氮，和其他污染物的排放，并在一图表中进行比较(Traffic grid calculation model of energy dissipation and pollution emissions, including carbon monoxide, nitrogen oxides, and other pollutants, and comparing in a chart)

文献 "Deblurring Text Images via L0-Regularized Intensity and Gradient Prior" 的参考代码 用Lp正则化方法做盲复原的代码 demo_text_deblurring 是主函数(refer to "Deblurring Text Images via L0-Regularized Intensity and Gradient Prior" main function: demo_text_deblurring)

说明：  用matlab写的分水岭算法用于图像分割写的不是很好有需要的看看吧(using Matlab was a watershed for image segmentation algorithm was not very good in need and let's see it)

这是本人发表的目标跟踪方面论文使用的代码，是基于随机假设概率滤波的多目标跟踪算法。(This is the code used by the target tracking paper I published, filter multi-target tracking algorithm based on the probability of a random assumption.)

说明：  一种图像阈值分割算法。能够对图像.sauvola是一种考虑局部均值亮度的图像二值化方法, 以局部均值为基准在根据标准差做些微调.算法实现上一般用积分图方法来实现.这个方法能很好的解决全局阈值方法的短板—关照不均图像二值化不好的问题.(Image threshold segmentation algorithm)

本例中主要使用四个区模糊函数对图像去模糊，分别是deconvwnr、deconvreg、deconvlucy、deconvblind。这四个函数分别适合不同的情况，对模糊图像的恢复效果也不同(In this case the main use of the four areas on the image to the fuzzy ambiguity function, respectively deconvwnr, deconvreg, deconvlucy, deconvblind. These four functions are appropriate for different situations, the recovery of the blurred image effect is different)