13 November 2003 On the choice of wavelet in image compression applications
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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.
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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); doi: 10.1117/12.507018; https://doi.org/10.1117/12.507018
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KEYWORDS
Wavelets

Image compression

Wavelet transforms

Data modeling

Error analysis

Quantization

Image processing

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