JPEG Still Image Data Compression Standard
JPEG Still Image Data Compression Standard
Adapted Total Variation for Artifact Free Decompression of JPEG Images
Journal of Mathematical Imaging and Vision
Fast Anisotropic Smoothing of Multi-Valued Images using Curvature-Preserving PDE's
International Journal of Computer Vision
Colorization in YCbCr color space and its application to JPEG images
Pattern Recognition
Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Color TV: total variation methods for restoration of vector-valued images
IEEE Transactions on Image Processing
Enhancement of Color Images by Scaling the DCT Coefficients
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
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This paper concerns color image restoration aiming at objective quality improvement of compressed color images in general rather than merely artifact reduction. In compressed color images, colors are usually represented by luminance and chrominance components. Considering characteristics of human vision system, chrominance components are generally represented more coarsely than luminance component. To recover such chrominance components, we previously proposed a model-based chrominance restoration algorithm where color images are modeled by a Markov random field. This paper presents a color image restoration algorithm derived by the MAP estimation, where all components are totally estimated. Experimental results show that the proposed restoration algorithm is more effective than the previous one.