By Topic

Bayesian Error Concealment With DCT Pyramid for Images

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Guangtao Zhai ; Inst. of Image Commun. & Inf. Process., Shanghai Jiao Tong Univ., Shanghai, China ; Xiaokang Yang ; Weisi Lin ; Wenjun Zhang

In this paper, the problem of concealing missing image blocks is casted into a framework of Bayesian estimation. The conditional expectation of the missing block vector is taken over a pilot vector of correctly decoded pixels near the missing block. Multiple observations of the missing vector and pilot vectors obtained in a neighborhood are used to approximate the expectation. We design a multiscale estimation approach with discrete cosine transform pyramid to improve estimation efficiency. The DC image of the missing block is recovered first, and then more details related to high-frequency AC coefficients are recovered successively. Moreover, the algorithm operates in an iterative mode through using estimated block to refine the searching process for the next estimation. The algorithm is found to perform very well for a wide range of block loss rates. Substantial improvement over 14 existing error concealment (inclusive of inpainting) algorithms on various images is demonstrated in our extensive experiments, under different test conditions inclusive of high-loss rates and large block sizes.

Published in:

Circuits and Systems for Video Technology, IEEE Transactions on  (Volume:20 ,  Issue: 9 )