DocumentCode
598197
Title
Algorithms for transform selection in multiple-transform video compression
Author
Xun Cai ; Lim, J.S.
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., Massachusetts Inst. of Technol., Cambridge, MA, USA
fYear
2012
fDate
Sept. 30 2012-Oct. 3 2012
Firstpage
2481
Lastpage
2484
Abstract
With a proper transform, an image or motion-compensated residual can be represented quite accurately with a small fraction of the transform coefficients. This is referred to as the energy compaction property. When multiple block transforms are used, selecting the best transform for each block that leads to the best energy compaction is difficult. In this paper, we develop two algorithms to solve this problem. The first algorithm, which is computationally simple, leads to a locally optimal solution. The second algorithm, which is more computationally intensive, gives a globally optimal solution. We discuss the algorithms and their performances. Two-dimensional discrete cosine transform (2-D DCT) and direction-adaptive one-dimensional discrete cosine transforms (1-D DCTs) are used to evaluate the performance of our algorithms. Results obtained are consistent with those from previous research.
Keywords
data compression; discrete cosine transforms; image motion analysis; video coding; 1D DCT; 2D DCT; image-compensated residual; motion-compensated residual; multiple block transforms; multiple-transform video compression; one-dimensional discrete cosine transforms; transform selection; two-dimensional discrete cosine transform; Algorithm design and analysis; Compaction; Convergence; Discrete cosine transforms; Signal processing algorithms; Video compression; Transforms; energy compaction; iterative algorithms; optimization; video compression;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing (ICIP), 2012 19th IEEE International Conference on
Conference_Location
Orlando, FL
ISSN
1522-4880
Print_ISBN
978-1-4673-2534-9
Electronic_ISBN
1522-4880
Type
conf
DOI
10.1109/ICIP.2012.6467401
Filename
6467401
Link To Document