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On holographic transform compression of images
Author(s) -
Bruckstein Alfred M.,
Netravali Arun N.
Publication year - 2000
Publication title -
international journal of imaging systems and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1098-1098
pISSN - 0899-9457
DOI - 10.1002/ima.1015
Subject(s) - discrete cosine transform , lossy compression , computer science , jpeg , quantization (signal processing) , transform coding , image compression , computer vision , artificial intelligence , lossless compression , image (mathematics) , algorithm , data compression , image processing
Lossy transform compression of images is successful and widespread. The JPEG standard uses the discrete cosine transform on blocks of the image and a bit allocation process that takes advantage of the uneven energy distribution in the transform domain. For most images, 10:1 compression ratios can be achieved with no visible degradations. However, suppose that multiple versions of the compressed image exist in a distributed environment such as the internet, and several of them could be made available upon request. The classical approach would provide no improvement in the image quality if more than one version of the compressed image became available. In this paper, we propose a method, based on multiple description scalar quantization, that yields decompressed image quality that improves with the number of compressed versions available. © 2001 John Wiley & Sons, Inc. Int J Imaging Syst Technol, 11, 292–314, 2000