New approach based on Shapiro’s embedded zero-tree wavelet algorithm for image compression

Ouafi, Abdelkrim; Baarir, Zine-Eddine; Taleb‐Ahmed, Abdelmalik; Doghmane, Noureddine; Zitouni, Athmane

doi:10.1117/1.2747590

Cited by 3 publications

(3 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The EZW encoder was developed by Shapiro [14] to encode an image, and since then, the EZW approach and its descendants have been studied [15,16]. The EZW encoder compresses data by utilizing the characteristic of an image transformed by DWT.…”

Section: Embedded Zerotree Wavelet Encodermentioning

confidence: 99%

“…The characteristic is that some detailed parts in different subbands are located in the same position in the image. As described in [15], two lists of coefficients are output through the encoding. Figure 4 shows parent-descendant relations in the image transformed three times, where the part distributions are the same as in Figure 2(g).…”

Section: Embedded Zerotree Wavelet Encodermentioning

confidence: 99%

“…This saves the memory space needed to describe descendants, resulting in data compression. As described in [15], two lists of coefficients are output through the encoding. One is the dominant list D, containing a series of four significance symbols assigned to each node.…”

Section: Embedded Zerotree Wavelet Encodermentioning

confidence: 99%

See 2 more Smart Citations

Wavelet‐based data compression for flow simulation on block‐structured Cartesian mesh

Sakai

Sasaki

Obayashi

et al. 2013

Numerical Methods in Fluids

View full text Add to dashboard Cite

SUMMARYA data compression method based on image encoding techniques is presented for a flow simulation data set. An input flow field data set is converted into the octree structure by discrete wavelet transform, and then quantized finely or coarsely depending on its importance in the flow field. Embedded zerotree wavelet encoding as the image encoding technique and entropy encoding reduce the data size by making use of the octree structure created previously. The present compression method is incorporated in a block‐structured Cartesian mesh method called Building‐Cube method. The Building‐Cube method gives not only good performance in the flow simulation but also consistency with the embedded zerotree wavelet encoding in the data compression. Three compression cases for incompressible and compressible flow simulations, including a large‐scale simulation with O(10 8) mesh points, demonstrate that the present compression method gives both high compression ratios and good qualities of compressed data. Copyright © 2013 John Wiley & Sons, Ltd.

show abstract

Section: Embedded Zerotree Wavelet Encodermentioning

confidence: 99%

Section: Embedded Zerotree Wavelet Encodermentioning

confidence: 99%

See 1 more Smart Citation

Wavelet‐based data compression for flow simulation on block‐structured Cartesian mesh

Sakai

Sasaki

Obayashi

et al. 2013

Numerical Methods in Fluids

View full text Add to dashboard Cite

show abstract

Lossless Colour Image Coding Using the Mojette Transform and Different Projections

Boukhari¹,

Schaefer

2014

2014 6th International Conference on Multimedia, Computer Graphics and Broadcasting

View full text Add to dashboard Cite

Low-memory-usage image coding with line-based wavelet transform

Guo

Nutter

et al. 2011

Opt. Eng

View full text Add to dashboard Cite

Abstract. When compared to the traditional row-column wavelet trans-form, the line-based wavelet transform can achieve significant memory savings. However, the design of an image codec using the line-based wavelet transform is an intricate task because of the irregular order in which the wavelet coefficients are generated. The independent block cod-ing feature of JPEG2000 makes it work effectively with the line-based wavelet transform. However, with wavelet tree-based image codecs, such as set partitioning in hierarchical trees, the memory usage of the codecs does not realize significant advantage with the line-based wavelet trans-form because many wavelet coefficients must be buffered before the cod-ing starts. In this paper, the line-based wavelet transform was utilized to facilitate backward coding of wavelet trees (BCWT). Although the BCWT algorithm is a wavelet tree-based algorithm, its coding order differs from that of the traditional wavelet tree-based algorithms, which allows the pro-posed line-based image codec to become more memory efficient than other line-based image codecs, including line-based JPEG2000, while still offering comparable rate distortion performance and much lower system complexity. C © 2011 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.3541802] Subject terms: image compression; line-based wavelet transforms; JPEG2000; wavelet trees. Paper 100746R received Sep. 12, 2010; revised manuscript received Dec. 9, 2010; accepted for publication Dec. 22, 2010; published online Feb. 14, 2011.

show abstract

New approach based on Shapiro’s embedded zero-tree wavelet algorithm for image compression

Cited by 3 publications

References 12 publications

Wavelet‐based data compression for flow simulation on block‐structured Cartesian mesh

Wavelet‐based data compression for flow simulation on block‐structured Cartesian mesh

Lossless Colour Image Coding Using the Mojette Transform and Different Projections

Low-memory-usage image coding with line-based wavelet transform

Contact Info

Product

Resources

About