five-methods-to-denoise

一份retinex算法的code，其中利用pca 做 色度分解，利用改进的bilateral滤波器进行低频和高频分解(Retinex algorithm in a code, which made use of PCA colority decomposition, the use of improved bilateral filter for low frequency and high-frequency decomposition)

将原始影像分别对RGB三色彩进行 x与 y轴之 Sobel边缘处理(original RGB images were of three colors for x and y axis of his Sobel Edge)

说明：  一、主要研究内容 1.基本内容 本设计目标在于利用Matlab强大的图像处理能力和实用便捷的编程方法，通过处理包含人脸的视频帧系列图像，灰度积分投影技术的眼睛定位方法，进而利用perclos计数，计算眨眼率，从而得到比较准确的疲劳状况。包括lun文初稿撰写。 2.具体要求 本设计基于灰度积分投影技术的眼睛定位方法，再结合perclos技术。首先通过图像预处理技术得到灰度分配较为均匀的图像,然后分别利用水平和垂直灰度积分投影曲线结合人脸的结构特征找到眼睛的位置坐标,实现了准确的眼睛定位,通过perclos技术技术眨眼率，根据先验值得到是否疲劳。 二、算法原理 视频输入——预处理去除非人脸区域——人脸定位——人眼定位（灰度积分投影）——眼睛张合度——perclos技术统计——输出结果 三、GUI界面设计 [需要有一定编程功底](1. Basic contents The goal of this design is to use the powerful image processing ability of MATLAB and the practical and convenient programming method, through processing the video frame series images including face, the eye location method of gray integral projection technology, and then using PERCLOS count to calculate the blink rate, so as to get a more accurate fatigue condition. Including the first draft of Lun.)

基于纹理度量的图像分割，适用于遥感图像，利用到K-mean算法(texture measurement based on the image segmentation, applicable to remote sensing images, the use of K-mean algorithm)

利用双线性插值和最近邻插值实现RGB图像的缩放，利用MATLAB编写(The use of bilinear interpolation and nearest neighbor interpolation to achieve RGB image scaling, using MATLAB to prepare)

sift算法引用于图像处理的一些常用程序(a reference to the image processing algorithms sift some common procedures)

提出了一种基于图像边缘连接的线段检测方法。数字图像中的线段是由很多线段图元组成,在同一 条线段中,它们的方向是相同的并且受到真实线段的方向约束。因此可以通过提取小的线段图元, 然后分析它们 的连接特性, 进行线段的检测。首先用ADM 算法对图像进行边缘检测, 得到单像素宽的边缘 然后在4 个方向上 进行线段的检测 对初步得到的结果进行合并和验证, 去掉短的线段, 连接临近的线段。经过实验证明, 该方法能 够快速地提取图像中的线段,并且对噪声具有一定的鲁棒性(A line segment connecting a detection method based on image edges. The segment of the digital image is composed by many segments elements, their orientation is the same and by the real line segment direction constraint in the same segment. By extracting a small segment Element can then analyze their connection characteristics for the detection of the line segment. First with ADM algorithm for edge detection on the image to obtain a single-pixel-wide edge then in the four directions on the detection of the line segments merger and verification of the preliminary results obtained, removing the short line segments, the line segments connected near. The experiments show that this method can quickly extract the line segments in the image, and certain robustness to noise)

图像融合中常用的评价指标（非常全面）如：平均梯度、相关系数、信息熵、交叉熵、联合熵、均方误差、互信息、信噪比、峰值信噪比、均方根误差、空间频率、标准差、均值、扭曲程度、偏差指数等等。(Image fusion evaluation (very comprehensive): average gradient, correlation coefficient, entropy, cross entropy, joint entropy, mean square error and mutual information, signal to noise ratio, peak signal to noise ratio, root mean square error, spacefrequency, standard deviation, mean, distorting the degree of deviation index.)

寻找照片PS痕迹的代码~大作业编写~可主要用于寻找添加图像块的PS边缘痕迹，(find the hint of a photo which has been PS)

特征提取: 提取了图像中各个标记区域的纹理特征及形状特征,标注详细(King Lek qiong 取: Joan 取了 Minghao Shilu rude plugging 各个标记区 的 理 Canton King Lek Lek 及 near Durian King, 标 downtown Circle Jiu)