An Efficient Codec for Image Compression Based on Spline Wavelet Transform and Improved SPIHT Algorithm

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

doi:10.1109/hpcs.2017.124

Cited by 3 publications

(1 citation statement)

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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%