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Visibility of Wavelet Quantization Noise
, 1996
"... The Discrete Wavelet Transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression. Measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coe ..."
Abstract

Cited by 145 (1 self)
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The Discrete Wavelet Transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression. Measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that we call DWT uniform quantization noise; it is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r 2 l , where r is display visual resolution in pixels/degree, and l is the wavelet level. Thresholds increase rapidly with wavelet spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from lowpass to horizontal/vertical to diagonal. We construct a mathematical model for DWT noise detection thresholds that is a function of level, orientation, and display visual resolution. This allows calculation of a "perceptually lossless" quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes.
DCT quantization noise in compressed images
 in Proc. Int. Conf. Image Process
, 2001
"... In lossy image compression schemes utilizing the discrete cosine transform (DCT), quantization of the DCT coefficients introduces error in the image representation and a loss of signal information. At high compression ratios, this introduced error produces visually undesirable compression artifacts ..."
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Cited by 25 (0 self)
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In lossy image compression schemes utilizing the discrete cosine transform (DCT), quantization of the DCT coefficients introduces error in the image representation and a loss of signal information. At high compression ratios, this introduced error produces visually undesirable compression artifacts that can dramatically lower the perceived quality of a particular image. This paper provides a spatial domain model of the quantization error based on a statistical noise model of the error introduced when quantizing the DCT coefficients. The resulting theoretically derived spatial domain quantization noise model shows that, in general, the compression noise in the spatial domain is both correlated and spatially varying. This provides some justification for many of the ad hoc artifact removal filters that have been proposed. An accurate description of quantization noise is essential if one hopes to remove, or at least alleviate, the visibility of compression artifacts. 1.
Perceptual optimization of DCT color quantization matrices,
 Proceedings of the IEEE International Conference on Image Processing,
, 1994
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