期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2008
卷号：XXXVII Part B2
页码：995-1000
出版社：Copernicus Publications
摘要：Many conventional contrast enhancement techniques adopt a global approach to enhance all the brightness level of the image. However, it is usually difficult to enhance all land cover classes appearing in the satellite images, because local contrast information and details may be lost in the dark and bright areas. In this study, a fuzzy-based image enhancement method is developed to partition the image pixel values into various degrees of associates in order to compensate the local brightness lost in the dark and bright areas. The algorithm contains three stages: First, the satellite image is transformed from gray-level space to membership space by Fuzzy c- Means clustering. Second, appropriate stretch model of each cluster is constructed based on corresponding memberships. Third, the image is transformed back to the gray-level space by merging stretched gray values of each cluster. Finally, the performance of the proposed scheme is evaluated visually and quantitatively. The results show that the proposed method can enhance the image to a quality visualization and superior index measurement
