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Lossless JPEG

About: Lossless JPEG is a research topic. Over the lifetime, 2415 publications have been published within this topic receiving 51110 citations. The topic is also known as: Lossless JPEG & .jls.


Papers
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Proceedings ArticleDOI
14 Mar 2010
TL;DR: This paper introduces some coding technologies proposed and applied to the G.711.0 codec, such as Plus-Minus zero mapping for the mapped domain linear predictive coding and escaped-Huffman coding combined with adaptive recursive Rice coding for lossless compression of the prediction residual.
Abstract: ITU-T Recommendation G.711.0 has just been established. It defines a lossless and stateless compression for G.711 packet payloads (for both A-law and μ-law). This paper introduces some coding technologies proposed and applied to the G.711.0 codec, such as Plus-Minus zero mapping for the mapped domain linear predictive coding and escaped-Huffman coding combined with adaptive recursive Rice coding for lossless compression of the prediction residual. Performance test results for those coding tools are shown in comparison with the results for the conventional technology. The performance is measured based on the figure of merit (FoM), which is a function of the trade-off between compression performance and computational complexity. The proposed tools improve the compression performance by 0.16% in total while keeping the computational complexity of encoder/decoder pair low (about 1.0 WMOPS in average and 1.667 WMOPS in the worst-case).

6 citations

Proceedings ArticleDOI
27 Apr 1995
TL;DR: An approach to exploiting the use of three distinct visual classes in mammograms directly for predictor choice by choosing the predictors adaptively depending on the context of surrounding pixel or predictor values is discussed.
Abstract: The JPEG lossless compression technique uses pixel value prediction based on the nearest neighbor pixel values. Usually a single predictor is used for the entire image. Recent work has shown that better compression performance can be achieved by choosing the predictors adaptively depending on the context of surrounding pixel or predictor values. This method is computationally lengthy and memory intensive. In mammograms the image contents can be separated into three distinct visual classes: background, smooth and textured, corresponding to three classes of predictors available in JPEG. This paper discusses an approach to exploiting the use of these classes directly for predictor choice.

6 citations

Proceedings ArticleDOI
03 Dec 2010
TL;DR: This paper proposes a realization of lossless-to-lossy image coding which has higher compatibility with JPEG standard than the conventional IntDCTs and is implemented by direct-lifting of DCT and inverse DCT (IDCT) and has high performance in lossless image coding.
Abstract: A discrete cosine transform (DCT) can be easily implemented in software and hardware for the JPEG and MPEG formats. Recently, some integer DCTs (IntDCTs) for lossless-to-lossy image coding have been proposed, but they do not satisfy enough compatibility with JPEG standard. This paper proposes a realization of lossless-to-lossy image coding which has higher compatibility with it than the conventional IntDCTs. Our IntDCT is implemented by direct-lifting of DCT and inverse DCT (IDCT) and has high performance in lossless image coding compared with any IntDCT while keeping high compatibility with JPEG standard. Finally, our method is validated by its application to lossless-to-lossy image coding.

6 citations

Proceedings ArticleDOI
27 Sep 1999
TL;DR: A new segmentation-based lossless compression method is proposed for color images that exploits the correlation existing among the three-color planes by treating each pixel as a vector of three components, and performing region growing and difference operations using the vectors.
Abstract: It is generally accepted that a color image may be encoded by using a gray-scale compression technique on each of the three-color planes. Such an approach, however, does not take advantage of the correlation existing between the color planes. In this paper, a new segmentation-based lossless compression method is proposed for color images. The method exploits the correlation existing among the three-color planes by treating each pixel as a vector of three components, and performing region growing and difference operations using the vectors. The method performed better than the Joint Photographic Experts Group (JPEG) standard by an average of 0.68 bit/pixel with a database including four natural color images of scenery, four images of burn wounds, and four fractal images. A transformation from the RGB planes to the luminance, in-phase, and quadrature-phase (YIQ) planes is applied, obtaining much better compression efficiency, given by 2.42 b/pixel over JPEG.

6 citations

Journal Article
TL;DR: This paper introduces some representative lossless data compression approaches and analyzes these kinds of data compression algorithms' advantages and disadvantages.
Abstract: With the quick increase of network's information,data compression is paid more and more attention by people.Data compression can be divided into two types,one is called lossless compression,and the other is called loss compression.It takes lossless data compression as main line.According to different compression technology of lossless data compression,from two aspects of statistic and dictionary ideas,it introduces some representative lossless data compression approaches and analyzes these kinds of data compression algorithms' advantages and disadvantages.Gather some mature betterment algorithm based on dictionary compression algorithm together and introduce them;It is facilitate reference for people who is interest in lossless data compression technology.

6 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202321
202240
20215
20202
20198
201815