Variance-based basis selection scheme for the gabor image transformation

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Abstract

This paper addresses the issues of time and compression efficiency in image transformation. We propose a novel basis selection scheme which improves transformation efficiency by exploiting the energy compacting characteristic in the frequency domain. In a typical complete transformation, a large number of basis functions have low coding efficiency, and thus are not necessary in the encoding process. By removing these functions from the basis set, we improve the time and the compression efficiency of the encoding process while maintaining a high reproduction quality. We have chosen to use the Gabor Transform to demonstrate our proposed method. Experimental results with the Gabor Transform are presented to demonstrate the effectiveness of our method. Finally, issues related to the application of this approach in image sequence encoding and the adaptation of our approach to other transformation schemes are discussed.

Original languageEnglish (US)
Pages (from-to)2205-2208
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume4
StatePublished - Jan 1 1995
EventProceedings of the 1995 20th International Conference on Acoustics, Speech, and Signal Processing. Part 2 (of 5) - Detroit, MI, USA
Duration: May 9 1995May 12 1995

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title = "Variance-based basis selection scheme for the gabor image transformation",
abstract = "This paper addresses the issues of time and compression efficiency in image transformation. We propose a novel basis selection scheme which improves transformation efficiency by exploiting the energy compacting characteristic in the frequency domain. In a typical complete transformation, a large number of basis functions have low coding efficiency, and thus are not necessary in the encoding process. By removing these functions from the basis set, we improve the time and the compression efficiency of the encoding process while maintaining a high reproduction quality. We have chosen to use the Gabor Transform to demonstrate our proposed method. Experimental results with the Gabor Transform are presented to demonstrate the effectiveness of our method. Finally, issues related to the application of this approach in image sequence encoding and the adaptation of our approach to other transformation schemes are discussed.",
author = "Patrick Lau and Papanikolopoulos, {Nikolaos P.}",
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N2 - This paper addresses the issues of time and compression efficiency in image transformation. We propose a novel basis selection scheme which improves transformation efficiency by exploiting the energy compacting characteristic in the frequency domain. In a typical complete transformation, a large number of basis functions have low coding efficiency, and thus are not necessary in the encoding process. By removing these functions from the basis set, we improve the time and the compression efficiency of the encoding process while maintaining a high reproduction quality. We have chosen to use the Gabor Transform to demonstrate our proposed method. Experimental results with the Gabor Transform are presented to demonstrate the effectiveness of our method. Finally, issues related to the application of this approach in image sequence encoding and the adaptation of our approach to other transformation schemes are discussed.

AB - This paper addresses the issues of time and compression efficiency in image transformation. We propose a novel basis selection scheme which improves transformation efficiency by exploiting the energy compacting characteristic in the frequency domain. In a typical complete transformation, a large number of basis functions have low coding efficiency, and thus are not necessary in the encoding process. By removing these functions from the basis set, we improve the time and the compression efficiency of the encoding process while maintaining a high reproduction quality. We have chosen to use the Gabor Transform to demonstrate our proposed method. Experimental results with the Gabor Transform are presented to demonstrate the effectiveness of our method. Finally, issues related to the application of this approach in image sequence encoding and the adaptation of our approach to other transformation schemes are discussed.

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