ROF-TV-denoising

实现一些图像的编辑功能，比如图像的打开，关闭，新建，删除，反转，等一些功能(Implement some image editing features, such as the image open, close, create, delete, reverse, and some other functions)

说明：  二进小波变换的图像增强,matlab代码(Dyadic wavelet transform image enhancement, matlab code)

复数乘法实现图像旋转，并且运用插值对旋转后的图像优化(Complex multiplication of image rotation, and the use of interpolation of the rotated image optimization)

传统图形细化算法，每条代码有详细注解，适合新手。(Traditional graphics thinning algorithm, each code have detailed notes. )

本人在写论文时自己编写的虹膜瞳孔的分割，采用二值化方法，并附有图片。希望有人和我一起研究。(I am writing papers prepared by his pupil iris division of the value of using two methods, accompanied by a caption. And I want people to see.)

C#实现了数字图像处理中的几个边缘检测的算法源代码。(C# implementation of digital image processing edge detection algorithm source code.)

一种基于DCT域盲数字水印嵌入程序，在DCT中频系数中嵌入水印，恢复時不用用到原始图像。(Based on DCT-domain blind digital watermark embedding process, in the intermediate frequency DCT coefficients to embed watermarks, when not used to restore the original image.)

ZhouZhiqiang2014年发表论文及源码，论文为基于多尺度加权梯度的多聚焦图像融合Multi-scale weighted gradient-based fusion for multi-focus images(Multi-scale weighted gradient-based fusion for multi-focus images)

jpeg压缩代码 An example for jpeg compression and the restoration。(The attached utility is a work I ve submitted to the university. It shows what a jpeg compression is all about.)

说明：  边缘检测是图像处理和计算机视觉中的基本问题，边缘检测的目的是标识数字图像中亮度变化明显的点。图像属性中的显著变化通常反映了属性的重要事件和变化。这些包括（i）深度上的不连续、（ii）表面方向不连续、（iii）物质属性变化和（iv）场景照明变化。边缘检测是图像处理和计算机视觉中，尤其是特征提取中的一个研究领域。 一阶:?Roberts Cross算子，Prewitt算子，Sobel算子， Kirsch算子，罗盘算子； 二阶： Marr-Hildreth，在梯度方向的二阶导数过零点，Canny算子，Laplacian算子。(Edge detection is a basic problem in image processing and computer vision. Significant changes in image attributes usually reflect significant events and changes in attributes. These include (I) discontinuities in depth, (ii) discontinuities in surface orientation, (iii) changes in material properties, and (iv) changes in scene lighting. Edge detection is a research field in image processing and computer vision, especially in feature extraction.)