Journal Article10.1142/S0218001488000236
Progress in high compression image coding
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TL;DR: This paper presents recent progress on some of the main avenues of object-based methods, which make use of contour-texture modeling, new results in neurophysiology and psychophisics and scene analysis, and second generation techniques.
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Abstract: The digital representation of an image requires a very large number of bits. The goal of image coding is to reduce this number, as much as possible, and to reconstruct a faithful duplicate of the original picture. Early efforts in image coding, solely guided by information theory, led to a plethora of methods. The compression ratio reached a plateau around 10: 1 a couple of years ago. Recent progress in the study of the brain mechanism of vision and scene analysis has opened new vistas in picture coding. Directional sensitivity of the neurones in the visual pathway combined with the separate processing of contours and textures has led to a new class of coding methods capable of achieving compression ratios as high as 100: 1. This paper presents recent progress on some of the main avenues of object-based methods. These second generation techniques make use of contour-texture modeling, new results in neurophysiology and psychophisics and scene analysis.
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Citations
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Picture processing: 1986
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•Dissertation
Segmentation-Based and Region-Adaptive Lossless Image Compression Underpinned by a Stellar-Field Image Model
Christian Dieter Grunler
- 01 Jan 2010
TL;DR: It is concluded that for archiving data, compression methods may indeed save costs for storage media or data transfer time, especially if a large part of the raw images is encoded with 32 bits per pixel.