Contrast enhancement technique based on local detection of edges
Computer Vision, Graphics, and Image Processing
Image and Video Compression Standards: Algorithms and Architectures
Image and Video Compression Standards: Algorithms and Architectures
Contrast enhancement using brightness preserving bi-histogram equalization
IEEE Transactions on Consumer Electronics
Minimum mean brightness error bi-histogram equalization in contrast enhancement
IEEE Transactions on Consumer Electronics
Properties and performance of a center/surround retinex
IEEE Transactions on Image Processing
Transform-based image enhancement algorithms with performance measure
IEEE Transactions on Image Processing
Compressed domain implementation of fuzzy rule-based contrast enhancement
FS'08 Proceedings of the 9th WSEAS International Conference on Fuzzy Systems
Computationally efficient algorithm for fuzzy rule-based enhancement on JPEG compressed color images
WSEAS Transactions on Signal Processing
Fuzzy intensification operator based contrast enhancement in the compressed domain
Applied Soft Computing
Combined de-noising and sharpening of color images in DCT domain
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
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A simple multi-scale image enhancement algorithm for compressing image dynamics and enhancing image details in the discrete cosine transform (DCT) domain is presented. First, an image is separated into illumination and reflectance components. Next, the illumination component is manipulated adaptively for image dynamics by using a content measure. The content measure using the energy distribution of the DCT coefficients is defined directly in each DCT block of an image. Then, the reflectance component is altered by a multi-scale @a-rooting method for enhancing image details based on human visual perception. The main advantage of the proposed algorithm enhances the details in the dark and the bright areas with low computations without boosting noise information and affecting the compressibility of the original image since it performs on the images in the compressed domain. In order to evaluate the proposed scheme, several base-line approaches are described and compared using enhancement quality measures.