JPEG Artifact Removal Using Error Distributions of Linear Coefficient Estimates

Authors:
Mika Inki
Affiliations:
Helsinki Institute for Information Technology, University of Helsinki FI-00014
Venue:
ICIAR '08 Proceedings of the 5th international conference on Image Analysis and Recognition
Year:
2008

Citing 6
Cited 0

The JPEG still picture compression standard

Communications of the ACM - Special issue on digital multimedia systems
Enhancement of JPEG-Compressed Images by Re-application of JPEG

Journal of VLSI Signal Processing Systems - Special issue on multimedia signal processing
Artifact reduction of JPEG coded images using mean-removed classified vector quantization

Signal Processing
Adapted Total Variation for Artifact Free Decompression of JPEG Images

Journal of Mathematical Imaging and Vision
Digital Image Processing (3rd Edition)

Digital Image Processing (3rd Edition)
Efficient DCT-domain blind measurement and reduction of blocking artifacts

IEEE Transactions on Circuits and Systems for Video Technology

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we present a method for JPEG artifact removal. The method works by estimating the distribution of a DCT coefficient given the values of the other coefficients, and then computing the expected value of this distribution in the quantization interval. We use information from an area exceeding the original block boundaries. Our method requires only information about image covariance, from which we estimate the effects of the transformations and quantization used in JPEG, under certain assumptions about the distributions. We will show that our method significantly improves the mean square error in our testing. Additionally, our method is shown to visibly reduce blocking artifacts in the images.