Linear pre/post filters for transform and subband/wavelet coding

Murching, A.M.; Woods, John W.

doi:10.1109/icip.1997.647377

Cited by 2 publications

(1 citation statement)

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“…In other cases, a PSD representation at a higher resolution than the given data is desired. Some examples of applications requiring such information are found in [9]- [11]. The proposed model and estimation offer some protection from corruption in requiring the PSD estimate to conform to a particular structure.…”

Section: Example Applicationmentioning

confidence: 98%

A Novel Parametric Power Spectral Density Model for Images

Prendergast¹,

Nguyen²

Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005.

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This paper introduces a novel power spectral density model for a class of images. This model is parametric with a variable number of parameters, and is easily defined in the correlation domain through the product of basic building blocks. By taking advantage of certain naturally occurring structural characteristics common to image power spectra, the result is capable of providing spectral detail that previous approaches could not. Consideration of these structural characteristics also allows accurate spectral estimates to be obtained even in the presence of some corruption and from low resolution data. That is, for typical images the model and estimation procedure provide a degree of robustness against some amounts of noise, distortion, and aliasing. The model and a numerical algorithm for estimating its parameters are presented along with some discussion and an example.

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Section: Example Applicationmentioning

confidence: 98%

A Novel Parametric Power Spectral Density Model for Images

Prendergast¹,

Nguyen²

Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005.

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Reconstruction error in transform/subband coding

Murching

Woods

Proceedings of International Conference on Image Processing

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We use the linear gain-plus-additive noise model for the class of pdf-optimized scalar quantizers to develop a frequency domain analysis of transform/subband coding systems. We derive a novel and explicit expression for the psd of the reconstruction error, and show that this psd has signal, alias and noise components. We employ this expression to compare different block transforms and subband filters with the rate-distortion optimal source coder, for a 1-D Gauss-Markov source. This paper quantifies, via the 'out-of-band' noise energy in the reconstruction error, the performance gap between DCT-based coders and coders that use subband/wavelet filters.

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Linear pre/post filters for transform and subband/wavelet coding

Cited by 2 publications

References 5 publications

A Novel Parametric Power Spectral Density Model for Images

A Novel Parametric Power Spectral Density Model for Images

Reconstruction error in transform/subband coding

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