当前位置: X-MOL 学术J. Ambient Intell. Human. Comput. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
An adaptive content based closer proximity pixel replacement algorithm for high density salt and pepper noise removal in images
Journal of Ambient Intelligence and Humanized Computing ( IF 3.662 ) Pub Date : 2020-07-30 , DOI: 10.1007/s12652-020-02376-2
K. Vasanth , R. Varatharajan

An Adaptive Content based Closer Proximity Pixel Replacement algorithm for the removal of high density salt and pepper noise in images is proposed. The algorithm uses decision tree to identify and correct the pixels of the image is noisy or not. The algorithm finds Euclidean distance between the processed pixel and the number of non-noisy pixels inside the current processing kernel. The algorithm requires only two non-noisy pixels to be present in kernel for the algorithm to operate. The faulty pixels are replaced only by the median of pixels that occurs more frequently in the current processing kernel based on the Euclidean distance. The algorithm increases the window size by two when there are no non-noisy pixels in the current processing kernel. The proposed algorithm was compared with 16 standard and existing algorithms derived from recent literatures. Exhaustive experiments on standard database images suggest that the algorithm exhibit excellent noise suppression and good information preservation characteristics even at very high noise densities.



中文翻译:

基于自适应内容的近距离像素替换算法,可去除图像中的高密度盐和胡椒噪声

提出了一种基于自适应内容的近距离像素替换算法,用于去除图像中的高密度盐和胡椒噪声。该算法使用决策树来识别和校正图像中是否有噪点的像素。该算法找到已处理像素与当前处理内核内部非噪点像素数之间的欧几里得距离。该算法只需要在内核中存在两个无噪点像素即可运行该算法。故障像素仅由基于欧几里德距离的当前处理内核中出现频率更高的像素中值替换。当前处理内核中没有无噪点像素时,该算法会将窗口大小增加两倍。将该算法与16种标准算法和现有算法进行了比较。在标准数据库图像上进行的详尽实验表明,即使在非常高的噪声密度下,该算法也具有出色的噪声抑制和良好的信息保存特性。

更新日期:2020-07-30
down
wechat
bug