boundary_trace

一段matlab试验程序，可以学习FFT+降噪的功能，适合初学者。(Test a matlab program, you can learn FFT+ noise reduction features, suitable for beginners.)

用fibonacci变换方法对图象做置乱或逆置乱，效率极高，在信息隐藏中属常用的方法之一。调用函数为f=fibonacci_t(I,r,s)，其中参数分别为I=被置乱的图像，r=置乱密钥，s=0置乱，s=1逆置乱(Fibonacci transformation method used to do on the image or inverse Scrambling Scrambling, high efficiency in the information hidden in one of the methods are commonly used. Call the function f = fibonacci_t (I, r, s), which parameters were I = have been scrambling the image, r = scrambling key, s = 0 Scrambling, s = 1 inverse Scrambling)

立体匹配，包括计算基本矩阵，极线校正，和SSD计算匹配点(Matching, including the calculation of fundamental matrix, epipolar correction, and SSD calculation of matching points)

对叶片进行预处理和提取部分特征：1.均值去噪 2.k均值聚类提取复杂背景下的叶子图片 3.填充孔洞 4.去叶柄 5.提取轮廓 6计算纵横轴比、面积凹凸比、周长凹凸比、球形性、圆形性、偏心率、形状参数和矩形度等特征值并进行画图。( Pretreatment of leaves and extract some of the characteristics: a mean denoising 2.k means clustering leaf extract complex background picture fill holes 3 4 5 contour extraction petiole 6 to calculate the vertical and horizontal axis ratio, convex area ratio.. convex perimeter than spherical, circularity, eccentricity, and rectangular shape parameter values ​ ​ and other characteristics of the drawing.)

用于数字图像处理的椒盐噪声滤波的自适应算法，(Salt and pepper for digital image processing adaptive noise filtering algorithm)

此代码为传统的snake模型算法代码，运行其中的egsnake.m即可。该代码实现对图像的边缘检测，仅供大家一块学习交流(This code is the code algorithm of traditional snake model, which can run egsnake.m. The code to achieve the image edge detection, we only a learning exchange.)

利用matlab对只包含RBG三个波段的图像进行植被提取，通过设定一定的阈值将植被与背景进行分割(The vegetation is extracted from the image containing only three bands of rbg by matlab, and the vegetation and background are segmented by setting a certain threshold.)

分享一个很好的图像处理MATLAB，代码最小全变差图像重建(Sharing a good image processing MATLAB, the code minimum total variation image reconstruction)

压缩感知重建算法,利用压缩感知理论实现用较少的采样量恢复出高分辨率的图像信息(compressive sensing reconstruction algoriyhm)

Matlab time-frequency analysis supporting the source code of chapter 12, please share