Spectral Information Recovery for Compressed Image Restoration

Author

Fu, Jingjing ; Wu, Feng ; Zeng, Bing

Author_Institution

Hong Kong Univ. of Sci. & Technol., Hong Kong

fYear

2008

fDate

25-27 March 2008

Firstpage

518

Lastpage

518

Abstract

In this paper, we attempt to solve the compressed image restoration by considering the recovery of spectral information in compressed images. For each NxN block in images, we convert the recovery problem to a route searching process in the N²-dimensional vector space R^N ² spanned by all DCT coefficients. The quantized DCT coefficients vectors A capped is known as the starting node of the route, while the target is original DCT coefficient vector A. In order to access A from A capped, a recovery route has to be built. Total variation (TV) based regularization can produce a group of estimated nodes by dynamic adjustment on images in spatial domain.

Keywords

data compression; discrete cosine transforms; image coding; image restoration; vector quantisation; compressed image restoration; discrete cosine transform; route searching process; spectral information recovery; total variation based regularization; vector quantisation; vector space; Algorithm design and analysis; Asia; Data compression; Discrete cosine transforms; Image coding; Image converters; Image restoration; Prediction algorithms; Quantization; TV; AC prediciton; copressed image restoration; regularization; spectral recovery;

fLanguage

English

Publisher

ieee

Conference_Titel

Data Compression Conference, 2008. DCC 2008

Conference_Location

Snowbird, UT

ISSN

1068-0314

Print_ISBN

978-0-7695-3121-2

Type

conf

DOI

10.1109/DCC.2008.59

Filename

4483345