A perceptually motivated three-component image model-part II: applications to image compression

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Abstract
In this paper, the use of the image model of Part I is investigated in the context of image compression, The model decomposes the image into a primary component that contains the strong edge information, a smooth component that represents the background slow-intensity variations, and a texture component that contains the textures, The primary component, which is known to be perceptually important, is encoded separately by encoding the intensity and geometric information of the strong edge brim contours, Two alternatives for coding the smooth and texture components are studied: entropy-coded adaptive DCT and entropy-coded subband coding, It is shown via simulations that the proposed schemes, which can be thought of as a hybrid of waveform coding and feature-based coding techniques, result in both subjective and objective performance improvements over several other image coding schemes and, in particular, over the JPEG continuous-tone image compression standard. These improvements are especially noticeable at low bit rates, Furthermore, it is shown that a perceptual tuning based on the contrast-sensitivity of the human visual system can be used in the DCT-based scheme, which in conjunction with the three-component model, leads to additional subjective performance improvements.

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