RANSAC-for-Outlier-Rejection

用于虹膜定位……定位外圆之前需要进行边界跟踪，此程序实现此功能(For Iris Location ... Location ... before the need for outer border tracking, this procedure realize this feature)

说明：  在稀疏域中，基于迭代阈值的线性反转问题，Daubechies 的经典外文文章，用于压缩感知(In the sparse domain, iterative threshold-based linear inversion problem, Daubechies classic foreign language articles for compressed sensing)

CVPR2013中出现的一种显著性特征检测算法，该算法用于模拟人眼视觉识别过程，提取图像中的显著性特征借后期目标对象的检测跟踪等使用，该算法(Context-Aware Saliency Detection。matlab implementation of an classical saliency detection alrogithm,which imitate our recognition process of eyes)

说明：  地形分块下的匹配导航算法仿真程序，算法包括最优分块算法和匹配定位算法的仿真(Simulation program of matching navigation algorithm under terrain block, including the simulation of optimal block algorithm and matching positioning algorithm)

matlab函数进行图像轮廓处理，处理效果还是可以的。(matlab function detect the picture and scale the picture)

分别利用均值滤波、自适应滤波和中值滤波对噪声图像g1和g2进行滤波，利用峰值信噪比对去噪性能进行比较。(Respectively, using the mean filter, adaptive filtering and median filtering images g1 and g2 noise filtering, denoising performance comparison using the peak signal-to-noise ratio.)

來自於2012年IEEE TIP的論文 Efficient Contrast Enhancement Using Adaptive Gamma Correction With Weighting Distribution ，其功能為透過分析影像中的直方圖統計資訊，達到快速增強影像對比的結果。(From the 2012 IEEE TIP paper "Efficient Contrast Enhancement Using Adaptive Gamma Correction With Weighting Distribution"which functions as a histogram of the image by analyzing statistical information, to quickly enhance image contrast.)

SURF的实现代码,用于图像特征提取，对于入门计算机视觉的同学有帮助(SURF implementation code for image feature extraction, for beginners of computer vision students help)

图像的逆滤波 维纳滤波 同时可以对图像进行模糊处理比如运动模糊 卷积模糊(Using C++ to complete images of conversion, processing and compression process, is to learn good reference digital image processing program!)

基于小波变换的人脸识别代码本代码对图像进行小波分解，然后又用最近邻方法实现了图像的识别。(Face Recognition Based on Wavelet Transform code-wavelet based face recognition, the code of the image wavelet decomposition, and then with the nearest neighbor method to achieve the image recognition!)