A Modified Embedded Zerotree Wavelet (MEZW) Algorithm for Image Compression

Ouafi, Abdelkrim; Ahmed, A. Taleb; Baarir, Zine-Eddine; Zitouni, Athmane

doi:10.1007/s10851-007-0057-y

Cited by 14 publications

(11 citation statements)

References 14 publications

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“…Losada et al modified Shapiro's Embedded Zerotree Wavelet algorithm (EZW) for image codec which is based on the Wavelet Transform and on the self-similarity inherent in images through applying a multi-iteration EZW to optimise the combination of ZT and Huffman coding [21]. Oufai et al proposed another modification of the EZW algorithm by using four symbols instead of using six as Shapiro's distributed the entropy in EZW and also optimized the coding by a binary grouping of elements before coding [22].…”

Section: Introductionmentioning

confidence: 99%

Chimera: A New Efficient Transform for High Quality Lossy Image Compression

2020

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A novel scheme is presented for image compression using a compatible form called Chimera. This form represents a new transformation for the image pixels. The compression methods generally look for image division to obtain small parts of an image called blocks. These blocks contain limited predicted patterns such as flat area, simple slope, and single edge inside images. The block content of these images represent a special form of data which be reformed using simple masks to obtain a compressed representation. The compression representation is different according to the type of transform function which represents the preprocessing operation prior the coding step. The cost of any image transformation is represented by two main parameters which are the size of compressed block and the error in reconstructed block. Our proposed Chimera Transform (CT) shows a robustness against other transform such as Discrete Cosine Transform (DCT), Wavelet Transform (WT) and Karhunen-Loeve Transform (KLT). The suggested approach is designed to compress a specific data type which are the images, and this represents the first powerful characteristic of this transform. Additionally, the reconstructed image using Chimera transform has a small size with low error which could be considered as the second characteristic of the suggested approach. Our results show a Peak Signal to Noise Ratio (PSNR) enhancement of 2.0272 for DCT, 1.179 for WT and 4.301 for KLT. In addition, a Structural Similarity Index Measure (SSIM) enhancement of 0.1108 for DCT, 0.051 for WT and 0.175 for KLT.

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Section: Introductionmentioning

confidence: 99%

Chimera: A New Efficient Transform for High Quality Lossy Image Compression

2020

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“…So, many attempts to enhance the EZW coder's features and to reduce its limitations have been suggested in the literature [15–21]. Our work focuses on the improvements done to the EZW and presented in [20, 21] and in [16].…”

Section: Introductionmentioning

confidence: 99%

“…In [20], the authors propose an efficient image coding method based on the use of a new significant symbol map in order to reduce the number of zerotrees [21]. Each one of the presented symbols is coded on three bits instead of two for the EZW.…”

Section: Introductionmentioning

confidence: 99%

Enhanced embedded zerotree wavelet algorithm for lossy image coding

Boujelbene

Boubchir

Jemâa

2019

IET Image Processing

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“…Particularly, several works have shown that EZW wavelet-based embedded image coders help to provide an excellent rate-distortion performance since dependencies of wavelet coefficients in subbands are well exploited for high resolution images [16][17][18]. However, in very low bit rate image coding using low resolution images (e.g., ROI size of 100×145) the embedded zerotree coding performance is prominently reduced due to the insufficient wavelet decomposition.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Medical Image Compression Based on Lossy and Lossless Embedded Zerotree Methods

Elhannachi¹,

Benamrane²,

Abdelmalik³

2017

J Inf Process Syst

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Since the progress of digital medical imaging techniques, it has been needed to compress the variety of medical images. In medical imaging, reversible compression of image's region of interest (ROI) which is diagnostically relevant is considered essential. Then, improving the global compression rate of the image can also be obtained by separately coding the ROI part and the remaining image (called background). For this purpose, the present work proposes an efficient reversible discrete cosine transform (RDCT) based embedded image coder designed for lossless ROI coding in very high compression ratio. Motivated by the wavelet structure of DCT, the proposed rearranged structure is well coupled with a lossless embedded zerotree wavelet coder (LEZW), while the background is highly compressed using the set partitioning in hierarchical trees (SPIHT) technique. Results coding shows that the performance of the proposed new coder is much superior to that of various state-of-art still image compression methods.

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A Modified Embedded Zerotree Wavelet (MEZW) Algorithm for Image Compression

Cited by 14 publications

References 14 publications

Chimera: A New Efficient Transform for High Quality Lossy Image Compression

Chimera: A New Efficient Transform for High Quality Lossy Image Compression

Enhanced embedded zerotree wavelet algorithm for lossy image coding

Adaptive Medical Image Compression Based on Lossy and Lossless Embedded Zerotree Methods

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