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Proceedings ArticleDOI

A fast algorithm for low-memory embedded wavelet-based image coding without list

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TLDR
A non-list coder together with subband selective algorithm is proposed with low-memory usage and fast encoding/decoding time and the PSNR performance of the proposed coder is slightly better than the list-based WDR.
Abstract
This paper proposes a new image coding technique with low-memory usage and fast encoding/decoding time In this embedded coder, the wavelet coefficients are tested with adaptive threshold and encoded into bit-stream with wavelet difference reduction (WDR) technique However, the original WDR is a list-based coder and needs quite a lot of memory during the encoding/decoding process Our new technique is non-list coder together with subband selective algorithm Non-list has reduced the memory requirement to only 1/4 times of the original image (from the 4–8 times of the list-based WDR) The subband selective technique reduces the number of coefficients to be tested in each bit-plane of significant pass thus computational time can be saved considerably, especially in high threshold bit-plane In order to have the coder with fast algorithm, simple raster scan is used in this coder Without any prediction scheme, the PSNR performance of the proposed coder is slightly better than the list-based WDR The simple prediction scheme increases PSNR to the same level as SPIHT Nevertheless, the favor of this coder is low-memory and fast computation speed The comparison of computational time between this non-list and list-based WDR is shown in the paper

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Citations
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Journal Article

Context modeled wavelet difference reduction coding based on fractional bit plane partitioning

TL;DR: This paper presents a new embedded wavelet image compression algorithm that is based on the wavelet difference reduction (WDR) method developed by Tian and Wells, and employs an adaptive scanning order that results from partitioning each bit-plane into multiple fractional bit-planes by exploiting intra-subband and inter- subband correlation.
Journal ArticleDOI

Efficient and simple scalable image compression algorithms

TL;DR: An algorithm that combines the low complexity and rate scalability features of the set partitioning coding approach, and it exploits the resolution scalability characteristics of the block-based systems to produce a highly scalable bit-stream.
Journal ArticleDOI

Efficient Scalable Image Compression Algorithms with Low Memory and Complexity

TL;DR: The main contribution of the first algorithm is that the amount of the algorithm’s usable memory is reduced to about 75% and at the same time its processing speed is increased and its rate distortion efficiency is preserved as will be demonstrated.

A Practical Wavelet Compression for Arbitrarily-Sized Natural Color Images

TL;DR: With its fast and memory-effective algorithm, the proposed coder performed at the same level as the JPEG2000 standard and significantly outperformed the existing JPEG standard for all test images which were downloaded from the Internet.
References
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Journal ArticleDOI

A new, fast, and efficient image codec based on set partitioning in hierarchical trees

TL;DR: The image coding results, calculated from actual file sizes and images reconstructed by the decoding algorithm, are either comparable to or surpass previous results obtained through much more sophisticated and computationally complex methods.
Journal ArticleDOI

Embedded image coding using zerotrees of wavelet coefficients

TL;DR: The embedded zerotree wavelet algorithm (EZW) is a simple, yet remarkably effective, image compression algorithm, having the property that the bits in the bit stream are generated in order of importance, yielding a fully embedded code.
Proceedings Article

A study of JPEG 2000 still image coding versus other standards

TL;DR: In this paper, the performance of JPEG 2000 versus JPEG-LS and MPEG-4 VTC, as well as the older but widely used JPEG, was evaluated by comparing the principles behind each algorithm.
Proceedings ArticleDOI

Embedded block coding in JPEG2000

TL;DR: The embedded block coding algorithm at the heart of the JPEG2000 image compression standard achieves excellent compression performance, usually somewhat higher than that of SPIHT with arithmetic coding, but in some cases substantially higher.
Proceedings ArticleDOI

SPIHT image compression without lists

TL;DR: A variant of the SPIHT image compression algorithm called no list SPIHT (NLS) is presented, which operates without linked lists and is suitable for a fast, simple hardware implementation.