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Performance analysis of hierarchical transform coding with a large kernel for video codecs
Author(s) -
Lee Bumshik,
Kim Munchurl,
Kim Hui Yong,
Choi Jin Soo
Publication year - 2014
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2012.0559
Subject(s) - transform coding , mathematics , algorithm , s transform , codec , artificial intelligence , kernel (algebra) , lapped transform , pattern recognition (psychology) , computer science , discrete cosine transform , wavelet transform , discrete wavelet transform , image (mathematics) , discrete mathematics , telecommunications , wavelet
In this study, the performance of hierarchical transform coding is analysed with design of an order‐16 integer transform kernel. The proposed hierarchical transform‐coding structure is constructed with a set of 4 × 4, 8 × 8 and 16 × 16 integer transforms of variable transform block sizes, which takes the advantages of both lower and higher transform kernels by flexibly adapting to varying image characteristics of video sequences with homogeneous and complex regions. The proposed hierarchical transform‐coding structure is implemented as an extension to H.264/advanced video coding joint model. The authors show the effectiveness of the hierarchical variable‐sized block transform scheme by analysing the quantisation effects and the correlation among neighbouring pixels in video sequences of different spatial resolutions. The experimental results show that: (i) the variable‐sized block transform scheme with the hierarchical structure is advantageous to the texture regions with strong local edges and (ii) the higher‐order‐16 integer transform kernel itself is more effective for the homogeneous texture regions, which are often encountered in higher resolution sequences. Therefore these two features can complementarily work in an rate‐distortion (RD) optimised manner for various characteristics of the input signals.

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