Topic
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.
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TL;DR: Wavelet methods have been shown to have no significant differences in diagnostic accuracy for compression ratios of up to 30:1, and the wavelet algorithm was found to have generally lower average error matrices and higher peak signal to noise ratios.
Abstract: Image compression is fundamental to the efficient and cost-effective use of digital medical imaging technology and applications. Wavelet transform techniques currently provide the most promising approach to high-quality image compression, which is essential for teleradiology and Picture Archiving and Communication System (PACS). In this study wavelet compression was applied to compress and decompress a digitized chest x-ray image at various compression ratios. The Wavelet Compression Engine (standard edition 2.5) was used in this study. This was then compared with the formal compression standard “Joint Photographic Expert Group” JPEG, using JPEG Wizard (standard edition 1.3.7). Currently there is no standard set of criteria for the clinical acceptability of compression ratio. Thus, histogram analysis, maximum absolute error (MAE), mean square error (MSE), root mean square error (RMSE), signal to noise ratio (SNR), and peak signal to noise ratio (PSNR) were used as a set of criteria to determine the ‘acceptability’ of image compression. The wavelet algorithm was found to have generally lower average error matrices and higher peak signal to noise ratios. Wavelet methods have been shown to have no significant differences in diagnostic accuracy for compression ratios of up to 30:1. Visual comparison was also made between the original image and compressed image to ascertain if there is any significant image degradation. Using wavelet algorithm, a very high compression ratio of up to 600:1 was achieved.
47 citations
01 Jan 2004
TL;DR: This paper investigates the scope of the intraframe coder of H.264 for image coding and compares the quality and the complexity of its decoder with the commonly used image codecs (JPEG and JPEG2000).
Abstract: The recently proposed H.264 video coding standard offers significant coding gains over previously defined standards. An enhanced intra-frame prediction algorithm has been proposed in H.264 for efficient compression of I-frames. This paper investigates the scope of the intraframe coder of H.264 for image coding. We compare the quality of this coder and the complexity of its decoder with the commonly used image codecs (JPEG and JPEG2000). Our results demonstrate that H.264 has a strong potential as an alternative to JPEG and JPEG2000.
47 citations
TL;DR: An overview of the key ideas behind the transform design in JPEG XR is provided, and how the transform is constructed from simple building blocks is described.
Abstract: JPEG XR is a draft international standard undergoing standardization within the JPEG committee, based on a Microsoft
technology known as HD Photo. One of the key innovations in the draft JPEG XR standard is its integer-reversible
hierarchical lapped transform. The transform can provide both bit-exact lossless and lossy compression in the same
signal flow path. The transform requires only a small memory footprint while providing the compression benefits of a
larger block transform. The hierarchical nature of the transform naturally provides three levels of multi-resolution signal
representation. Its small dynamic range expansion, use of only integer arithmetic and its amenability to parallelized
implementation lead to reduced computational complexity. This paper provides an overview of the key ideas behind the
transform design in JPEG XR, and describes how the transform is constructed from simple building blocks.
47 citations
TL;DR: The performance of state-of-the-art lossless image coding methods can be considerably improved by a recently introduced preprocessing technique that can be applied whenever the images have sparse histograms, and this letter addresses this issue.
Abstract: The performance of state-of-the-art lossless image coding methods [such as JPEG-LS, lossless JPEG-2000, and context-based adaptive lossless image coding (CALIC)] can be considerably improved by a recently introduced preprocessing technique that can be applied whenever the images have sparse histograms. Bitrate savings of up to 50% have been reported, but so far no theoretical explanation of the fact has been advanced. This letter addresses this issue and analyzes the effect of the technique in terms of the interplay between histogram packing and the image total variation, emphasizing the lossless JPEG-2000 case.
47 citations
22 Aug 2005
TL;DR: This is the first comprehensive study of standard JPEG2000 compression effects on face recognition, as well as an extension of existing experiments for JPEG compression.
Abstract: In this paper we analyse the effects that JPEG and JPEG2000 compression have on subspace appearance-based face recognition algorithms. This is the first comprehensive study of standard JPEG2000 compression effects on face recognition, as well as an extension of existing experiments for JPEG compression. A wide range of bitrates (compression ratios) was used on probe images and results are reported for 12 different subspace face recognition algorithms. Effects of image compression on recognition performance are of interest in applications where image storage space and image transmission time are of critical importance. It will be shown that not only that compression does not deteriorate performance but it, in some cases, even improves it slightly. Some unexpected effects will be presented (like the ability of JPEG2000 to capture the information essential for recognizing changes caused by images taken later in time) and lines of further research suggested.
47 citations