文章基本信息

标题：Bit Reduced FCM with Block Fuzzy Transforms for Massive Image Segmentation
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作者：Barbara Cardone ; Ferdinando Di Martino
期刊名称：Information
电子版ISSN：2078-2489
出版年度：2020
卷号：11
期号：7
页码：1-18
DOI：10.3390/info11070351
出版社：MDPI Publishing
摘要：A novel bit reduced fuzzy clustering method applied to segment high resolution massive images is proposed. The image is decomposed in blocks and compressed by using the fuzzy transform method, then adjoint pixels with same gray level are binned and the fuzzy c-means algorithm is applied on the bins to segment the image. This method has the advantage to be applied to massive images as the compressed image can be stored in memory and the runtime to segment the image are reduced. Comparison tests are performed with respect to the fuzzy c-means algorithm to segment high resolution images; the results shown that for not very high compression the results are comparable with the ones obtained applying to the fuzzy c-means algorithm on the source image and the runtimes are reduced by about an eighth with respect to the runtimes of fuzzy c-means.
关键词：fuzzy c-means (FCM); bit-reduced fuzzy c-means (brFCM); Fuzzy Transform bit reduction FCM clustering algorithm (FTbrFCM); massive data; image segmentation fuzzy c-means (FCM) ; bit-reduced fuzzy c-means (brFCM) ; Fuzzy Transform bit reduction FCM clustering algorithm (FTbrFCM) ; massive data ; image segmentation