On the choice of wavelet in image compression applications

Kameswara Rao Namuduri

doi:10.1117/12.507018

13 November 2003 On the choice of wavelet in image compression applications

Kameswara Rao Namuduri

Proceedings Volume 5207, Wavelets: Applications in Signal and Image Processing X; (2003) https://doi.org/10.1117/12.507018
Event: Optical Science and Technology, SPIE's 48th Annual Meeting, 2003, San Diego, California, United States

Abstract

Data decorrelation and energy compaction are the two fundamental characteristics of wavelets that led to wavelet based image compression models. Wavelet transform is not a perfect whitening transform; but it is viewed as an approximation to Karhunen-Loeve transform (KLT). In general, decorrelation does not imply statistical independence. Thus, a wavelet transform results in coefficients which exhibit inter and intra band dependencies. The energy compaction property of a wavelet is reflected in the coding performance, which can be measured by its coding gain. This paper investigates the above two important aspects of bi-orthogonal wavelets in the context of lossy compression. This investigation suggests that simple predictive models are sufficient to capture the dependencies exhibited by the wavelet coefficients. This paper also compares the metrics that measure the performance of bi-orthogonal wavelets in lossy coding schemes.

Citation Download Citation

Kameswara Rao Namuduri "On the choice of wavelet in image compression applications", Proc. SPIE 5207, Wavelets: Applications in Signal and Image Processing X, (13 November 2003); https://doi.org/10.1117/12.507018

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