Toward an optimal B-spline wavelet transform for image compression

Boujelbene, Rania; Jemâa, Yousra Ben; Zribi, Mourad

doi:10.1109/aiccsa.2016.7945738

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…The experiments have been tested for image compression, and the results show comparable performance with respect to the other state-of-the-art wavelets. More recently, in [51,52] the authors have extended the previous cited work by considering a larger set of configurations, focusing on the search for the best order of the filters. Since their performance is quite interesting for compression, we include some of these new bi-orthogonal wavelets in our overall analysis.…”

Section: Orthonormalitymentioning

confidence: 99%

A wavelet filter comparison on multiple datasets for signal compression and denoising

Gnutti

Guerrini

Adami

et al. 2021

Multidim Syst Sign Process

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In this paper, we explicitly analyze the performance effects of several orthogonal and bi-orthogonal wavelet families. For each family, we explore the impact of the filter order (length) and the decomposition depth in the multiresolution representation. In particular, two contexts of use are examined: compression and denoising. In both cases, the experiments are carried out on a large dataset of different signal kinds, including various image sets and 1D signals (audio, electrocardiogram and seismic). Results for all the considered wavelets are shown on each dataset. Collectively, the study suggests that a meticulous choice of wavelet parameters significantly alters the performance of the above mentioned tasks. To the best of authors' knowledge, this work represents the most complete analysis and comparison between wavelet filters. Therefore, it represents a valuable benchmark for future works.

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Section: Orthonormalitymentioning

confidence: 99%

A wavelet filter comparison on multiple datasets for signal compression and denoising

Gnutti

Guerrini

Adami

et al. 2021

Multidim Syst Sign Process

View full text Add to dashboard Cite

show abstract

“…The authors of paper [4] present a new biorthogonal wavelet transform using splines performed in a 'lifting' manner. Specifically, polynomial splines of different order were used in the lifting constructions.…”

Section: Introductionmentioning

confidence: 99%

Spaces of polynomial and nonpolynomial spline-wavelets

et al. 2019

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This paper, discusses spaces of polynomial and nonpolynomial splines suitable for solving the Hermite interpolation problem (with first-order derivatives) and for constructing a wavelet decomposition. Such splines we call Hermitian type splines of the first level. The basis of these splines is obtained from the approximation relations under the condition connected with the minimum of multiplicity of covering every point of (α, β) (almost everywhere) with the support of the basis splines. Thus these splines belong to the class of minimal splines. Here we consider the processing of flows that include a stream of values of the derivative of an approximated function which is very important for good approximation. Also we construct a splash decomposition of the Hermitian type splines on a non-uniform grid.

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