Title
Redefined Block-Lifting-based Filter Banks with Efficient Reversible Nonexpansive Convolution
Abstract
This paper redefines a block-lifting structure of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> -channel ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M\in \mathbb {N}$ </tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M\geq 2$ </tex-math></inline-formula> ) filter banks and proposes an efficient reversible nonexpansive convolution at the boundaries for lossy-to-lossless image coding. The previous studies left two problems. One is that the conventional lifting-based filter banks (FBs) are restricted to having equal analysis/synthesis filter lengths. We derive block-lifting-based FBs (BLFBs) with not only equal analysis/synthesis filter lengths but also the longer synthesis filter lengths than those of the analysis banks. The other problem is that the conventional lifting-based FBs without the linear-phase property, such as BLFBs, cannot implement the conventional smooth nonexpansive convolution at the boundaries because of the rounding error in each lifting. We solve the boundary problem by using an efficient reversible nonexpansive convolution derived from a nonexpansive convolution for nonlinear-phase FBs with paraunitariness. We show that the redefined BLFBs with the efficient reversible nonexpansive convolution perform well at lossy-to-lossless image coding.
Year
DOI
Venue
2019
10.1109/tcsvt.2018.2849101
IEEE Transactions on Circuits and Systems for Video Technology
Keywords
Field
DocType
Image coding,Convolution,Transform coding,Filter banks,Discrete wavelet transforms,Symmetric matrices
Pattern recognition,Round-off error,Convolution,Computer science,Transform coding,Communication channel,Algorithm,Image coding,Symmetric matrix,Artificial intelligence,Boundary problem
Journal
Volume
Issue
ISSN
29
5
1051-8215
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Taizo Suzuki110420.45
Naoki Tanaka292.55
H Kudo3165.29