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• W2134792226 abstract "The most popular lossy image compression method used on the Internet is the JPEG standard. JPEG's good compression performance and low computational and memory complexity make it an attractive method for natural image compression. Nevertheless, as we go to low bit rates that imply lower quality, JPEG introduces disturbing artifacts. It is known that, at low bit rates, a down-sampled image, when JPEG compressed, visually beats the high resolution image compressed via JPEG to be represented by the same number of bits. Motivated by this idea, we show how down-sampling an image to a low resolution, then using JPEG at the lower resolution, and subsequently interpolating the result to the original resolution can improve the overall PSNR performance of the compression process. We give an analytical model and a numerical analysis of the down-sampling, compression and up-sampling process, that makes explicit the possible quality/compression trade-offs. We show that the image auto-correlation can provide a good estimate for establishing the down-sampling factor that achieves optimal performance. Given a specific budget of bits, we determine the down-sampling factor necessary to get the best possible recovered image in terms of PSNR." @default.
• W2134792226 created "2016-06-24" @default.
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• W2134792226 creator A5091366774 @default.
• W2134792226 date "2003-09-01" @default.
• W2134792226 modified "2023-10-11" @default.
• W2134792226 title "Down-scaling for better transform compression" @default.
• W2134792226 cites W1634005169 @default.
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• W2134792226 doi "https://doi.org/10.1109/tip.2003.816023" @default.
• W2134792226 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/18237984" @default.
• W2134792226 hasPublicationYear "2003" @default.
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