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Proceedings Paper

DCT computation with minimal average number of operations
Author(s): Krisda Lengwehasatit; Antonio Ortega
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Paper Abstract

The discrete cosine transform (DCT) is widely used in all transform-based image and video compression standards due to its well-known decorrelation and energy compaction properties for typical images. Many fast algorithms available for the DCT optimize various parameters such as additions and multiplications but they are input independent and thus require the same number of operations for any inputs. In this paper we study the benefits of input- dependent algorithms for the DCT which are aimed at minimizing the average computation time by taking advantage of the sparseness of the input data. Here, we concentrate on the inverse DCT (IDCT) part since typical input blocks will contain a substantial number of zeros. We show how to construct an IDCT algorithm based on the statistics of the input data, which are used to optimize the algorithm for the average case. We show how, for a given input and a correct model of the complexity of the various operations, we can achieve the fastest average performance.

Paper Details

Date Published: 10 January 1997
PDF: 12 pages
Proc. SPIE 3024, Visual Communications and Image Processing '97, (10 January 1997); doi: 10.1117/12.263291
Show Author Affiliations
Krisda Lengwehasatit, Univ. of Southern California (United States)
Antonio Ortega, Univ. of Southern California (United States)

Published in SPIE Proceedings Vol. 3024:
Visual Communications and Image Processing '97
Jan Biemond; Edward J. Delp III, Editor(s)

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