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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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Journal ArticleDOI
TL;DR: The analysis of texture in video-stored echocardiographic images is an established method to characterize myocardial pathologies and it is concluded that texture of video-Stored images is not comparable to that of digitally-storied images and that JPEG compression changes important second-order texture parameters.
Abstract: The analysis of texture in video-stored echocardiographic images is an established method to characterize myocardial pathologies. We investigated whether or not texture parameters calculated from video-stored images and those derived from the joint photographic expert group (JPEG) format compressed data are equivalent to those calculated from uncompressed digital images. Texture parameters were calculated using uncompressed digital data, images stored on videotape, and three forms of compressed digital data (baseline JPEG, JPEG 2000 and lossless JPEG 2000). Video storage heavily affected most texture parameters. Although first-order texture parameters derived from JPEG-compressed images were generally equivalent to those derived from the uncompressed data, several second-order parameters differed significantly. We conclude that texture of video-stored images is not comparable to that of digitally-stored images and that JPEG compression changes important second-order texture parameters. This observation should be taken into account when analyzing texture of modern image data (uncompressed or compressed) and comparing the results with earlier studies utilizing video-stored data.

2 citations

Proceedings Article
Guang Deng1
01 Sep 1998
TL;DR: Results show that for a set of 18 images of different kinds, the compression performance of the proposed algorithm is very close to that of CALIC and is better than LOCO and S+P.
Abstract: In this paper a context based lossless image compression algorithm is presented It consist of an adaptive median-FIR predictor, a conditional context based error feed back process and a new error representation The prediction error is encoded by a context-based arithmetic encoder Experimental results show that for a set of 18 images of different kinds, the compression performance of the proposed algorithm is very close to that of CALIC and is better than LOCO and S+P This paper also presents an algorithmic study of the proposed algorithm The contribution of each of the building blocks to the compression performance is studied It has been shown that these building blocks can be incorporated into further development of lossless image compression algorithms

1 citations

Proceedings ArticleDOI
08 Dec 2011
TL;DR: This paper presents a method to improve the transmitting rate with the unchanged reliability for ghost-imaging system based on entanglement, and shows that when the compression ratio of JPEG is beyond the coding efficiency of linear block codes, it can get some gains of the image with Peak Signal-to-Noise Ratio increase.
Abstract: Ghost imaging has attracted a lot of attentions recently, but the trade-off between the reliability and the transmitting rate becomes the biggest challenge for ghost imaging. In this paper, we present a method to improve the transmitting rate with the unchanged reliability for ghost-imaging system based on entanglement. In the scheme, we first encode the image by Joint Photographic Experts Group (JPEG) algorithm before transmitting an image, and then encode the JPEG bits stream using linear block codes to overcome the lossy information by compression. The transmitting rate can be enhanced by compression, and the reliability can be kept by linear block codes. By experiments, the results show that when the compression ratio of JPEG is beyond the coding efficiency of linear block codes, we can get some gains of the image with Peak Signal-to-Noise Ratio(PSNR) increase. Compared with direct transmission bit stream, our scheme can improve the PSNR 16dB, using 1.225 times of the transmission times.

1 citations

Proceedings ArticleDOI
16 Nov 2005
TL;DR: Experimental results on different types of music and songs show a new competitive compression ratio compared to the other algorithms of the lossless audio compression.
Abstract: In this paper a new predictive lossless coding scheme is proposed. The prediction is based on a cascaded peak to valley linear prediction method (PVLP). This method is based on simple linear prediction between the detected feature points. Experimental results on different types of music and songs show a new competitive compression ratio compared to the other algorithms of the lossless audio compression.

1 citations


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