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 4 publications

(2 citation statements)

References 17 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

“…Encoding is performed from the highest to lowest magnitude. On computing the wavelet transform of the image, the wavelet is partitioned into spatial oriented trees by SPIHT [7]. Multiple nodes are used for arrangement of the trees and each node corresponds to each pixel.…”

Section: Introductionmentioning

confidence: 99%

Implementation of FPGA hardware architecture for optimized SPIHT coder using 2DWT-A

2022

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During multimedia communication and in Health care IOT, we transmit medical images and other information to health care experts, caretakers and relatives with faster speed. Remote monitoring gains periodical data and can be transported to the cloud due to its massive nature. This huge data can accommodate larger bandwidth and reduces the speed of operation. Hence, image compression is crucial for multimedia data communication. The proposed work develops an integrated architecture for both image transform and SPIHT based encoding process. We have selected the SPIHT algorithm for image compression because of its several expedient features. Parallel pipelined poly-phase two dimensional discrete wavelet transform based image transform architecture has been designed and implemented with reduced hardware and latency. The SPIHT encoder receives the low frequency components from the 2DWT-A image transformer. We removed other high frequency components to reduce the number of coefficients for transmission. In SPIHT encoder architecture, the hardware efficient binary arithmetic encoder with position control unit is used to avoid prefix zeros during arithmetic computation which replaces the hardware expensive arithmetic coders. This increases the speed of operation of the image codec. This brings effective hardware utilization into focus. Xilinx FPGA device with Microblaze core processor and SPARTAN 3EDK kit is used for realization of the hardware architecture. We use image codec architecture enactment principle for examination. We compare the performance of the proposed architecture with the existing schemes. The requirements, power and delay for the proposed method are optimized considerably when compared to the existing techniques. It reduces the area of the designed system while increasing the frequency by a factor of 2.1MHz. We use 180nm CMOS technology in Cadence tool for estimating the performance at cell level.

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An Efficient Image Codec Using Spline-Based Directional Lifting Wavelet Transform and an Optimized EZW Algorithm

Boujelbene¹,

Jemâa²

2021

Advanced Information Networking and Applications

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

Cited by 4 publications

References 17 publications

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

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

Implementation of FPGA hardware architecture for optimized SPIHT coder using 2DWT-A

An Efficient Image Codec Using Spline-Based Directional Lifting Wavelet Transform and an Optimized EZW Algorithm

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