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Lossless Compression of Medical Images by Content-Driven Laplacian Pyramid Splitting (Contributo in volume (capitolo o saggio))

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Lossless Compression of Medical Images by Content-Driven Laplacian Pyramid Splitting (Contributo in volume (capitolo o saggio)) (literal)

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B. Aiazzi; L. Alparone; S. Baronti (1996)
Lossless Compression of Medical Images by Content-Driven Laplacian Pyramid Splitting
Springer-Verlag, Berlin/Heidelberg (Germania) in Image Technology: Advances in Image Processing, Multimedia and Machine Vision, 1996
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http://books.google.it/books?id=ZD3CrhDw-mgC&pg=PA595&lpg=PA595&dq=Image+Technology,+Advances+in+Image+Processing,+Multimedia+and+Machine+Vision+Lossless+compression+of+medical+images+by+content-driven+Laplacian+pyramid+splitting&source=bl&ots=YP1B3KNGRY&sig=NO-55bHz6rmaemks9XRLntsFXkk&hl=it&sa=X&ei=fTKhT5G-G6qI4gTN8PjkCA&ved=0CCQQ6AEwAQ#v=onepage&q=Image%20Technology%2C%20Advances%20in%20Image%20Processing%2C%20Multimedia%20and%20Machine%20Vision%20Lossless%20compression%20of%20medical%20images%20by%20content-driven%20Laplacian%20pyramid%20splitting&f=false (literal)

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Image Technology: Advances in Image Processing, Multimedia and Machine Vision (literal)

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Istituto di Ricerca sulle Onde Elettromagnetiche \"Nello Carrara\", Italian National Research Council, IROE-CNR, via Panciatichi 64, I-50127 Florence, Italy Dipartimento di Ingegneria Elettronica, University of Florence, via di S. Marta 3, I-50139 Florence, Italy Istituto di Ricerca sulle Onde Elettromagnetiche \"Nello Carrara\", Italian National Research Council, IROE-CNR, via Panciatichi 64, I-50127 Florence, Italy (literal)

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Lossless Compression of Medical Images by Content-Driven Laplacian Pyramid Splitting (literal)

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Abstract

An efficient scheme based on an enhanced Laplacian pyramid (LP) is proposed for lossless/lossy compression and progressive transmission of medical images. The entropy of the LP is reduced by adopting two filters different for reduction and expansion. Encoding priority is given to major details through a hierarchical content-driven decision rule defining a binary quad-tree of split nodes, which is run-length encoded. The root layer of the pyramid is optimally chosen for spatial DPCM encoding. Error feedback along the layers of the LP ensures lossless and semi-lossy reconstruction capability and improves the robustness of the overall scheme. Reversible compression of scanned RX images, achieved at ratios of about 6:1, establish improvements over both DPCM and pyramid schemes. High-quality lossy versions at 60:1 compression ratio outperform JPEG both visually and quantitatively. Also results of NMR images are presented and discussed. (literal)

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