IICandIID_R_nmp

此文件是关于图像处理中灰度视频播放等相关知识的综合运用。(it is about the gray in image processing)

基于遗传算法的图像分割算法。实现图像的分割，显示原图及处理结果图像。(Based on genetic algorithm image segmentation algorithm. Realize image segmentation, and processing results show the image. )

说明：   最简单的差分格式有向前、向后和中心3种。 向前差分：f (n)=f(n+1)-f(n) 向后差分：f (n)=f(n)-f(n-1) 中心差分：f (n)=[f(n+1)-f(n-1)]/2(The easiest difference format forward, backward, and three kinds of centers. Forward differencing: f (n) = f (n+ 1)-f (n) Backward difference: f (n) = f (n)-f (n-1) Central difference: f (n) = [f (n+ 1)-f (n-1)]/2)

图像去噪，小波硬阈值滤波，sym4小波基函数(Image denoising and hard threshold wavelet filtering, sym4 wavelet basis function )

不均匀光照下的文字分割，综合运用同态滤波方法、Bernsen局部阈值法、边缘识别法。(Uneven illumination of the text segmentation, integrated use of homomorphic filtering methods, Bernsen local threshold, the edge identification method.)

说明：  IQA评估指标包括PLCC，SROCC，KROCC，PSNR，SSIM (Structural Similarity），MSE (Mean Square Error)，RMSE (Root Mean Square Error) ，信息熵 (Information Entropy)算法(IQA evaluation indicators include PLCC, SROCC, KROCC, PSNR, SSIM (Structural Similarity), MSE (Mean Square Error), RMSE (Root Mean Square Error) , Information Entropy (Information Entropy) algorithm)

Tae Hoon Kim教授的Nonparametric Higher-Order Learning for Interactive Segmentation源码(Tae Hoon Kim, Professor Nonparametric Higher-Order Learning for Interactive Segmentation)

骨骼图像增强，对应于冈萨雷斯数字图像处理教程上的五个步骤(Bone image enhancement, digital image processing corresponding to Gonzalez' s five-step Tutorial)

Poission_image_editing对应的GUI程序，可实现图像的无缝融合。(Poission_image_editing corresponding GUI program can achieve the seamless integration of the image.)

说明：  数字图像处理（中译）第三版-冈萨雷斯 书籍配套PPT(digital image processing)