University of South Carolina 1997 : 02 Data compression and elementary encoding of wavelet coefficients
نویسندگان
چکیده
Two elementary algorithms are introduced for image compression each of which is based on efficient, lossless encoding of quantized bi-orthogonal wavelet coefficients. Application of this type of algorithm is applied to several standard test images using regular and hyperbolic wavelet bases, and comparisons are given to Shapiro’s EZW algorithm. Peak signal to noise ratio improvements typically of 0.6–0.8 dB are demonstrated. Generalizations of this type of algorithm to non-square images and higher dimensions are also briefly described.
منابع مشابه
Context modeling and entropy coding of wavelet coefficients for image compression
In this paper we study the problem of context modeling and entropy coding of the symbol streams generated by the well-known EZW image coder (embedded image coding using zerotrees of wavelet coe cients). We present some simple context modeling techniques that can squeeze out more statistical redundancy in the wavelet coe cients of EZW-type image coders and hence lead to improved coding e ciency.
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