Active Computer Vision by Cooperative Focus and Stereo
Active Computer Vision by Cooperative Focus and Stereo
Digital Image Processing
ICCSIT '08 Proceedings of the 2008 International Conference on Computer Science and Information Technology
Contrast enhancement using brightness preserving bi-histogram equalization
IEEE Transactions on Consumer Electronics
A robust approach to image enhancement based on fuzzy logic
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
An Optimal Fuzzy System for Color Image Enhancement
IEEE Transactions on Image Processing
A fuzzy operator for the enhancement of blurred and noisy images
IEEE Transactions on Image Processing
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In this paper, we have performed a comparative analysis of various conventional contrast enhancement techniques (histogram equalisation and adaptive histogram equalisation), the recent fast grey-level grouping method (Chen et al., 2006a,b), the fuzzy logic method (Hanmandlu and Jha, 2006) and a modified fuzzy logic method (Nair et al., in press) to find out which of these is well suited for automatic contrast enhancement for satellite images of the ocean, obtained from a variety of sensors. The principle of transforming the skewed histogram of the original image into a uniform histogram is used as the basis for all techniques. The performance of the different contrast enhancement algorithms is evaluated based on the visual quality and the Tenengrad criterion. The inter-comparison of different techniques was carried out on a standard low contrast image and also on different satellite images with different characteristics. Based on our study, we conclude that the modified fuzzy logic (Nair et al., in press) is well suited for automatic contrast enhancement of satellite images of the ocean.