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A Perceptually Motivated Three-Component Image Model

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Video Coding

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Abstract

Some psychovisual properties of the human visual system (HVS) are discussed and interpreted in a mathematical framework. The formation of perception on monocular images is described by minimization problems based on the special properties of human binocular vision. The edge information, which is found to be of primary importance in visual perception, forms the constraint in the minimization problems. The smooth areas of an image influence human perception together with the edge information. After the concept of edge strength is introduced, it is demonstrated that strong edges are of higher perceptual importance than weaker edges (textures). The notion of a stressed image is introduced and used in the extraction of strong edges; the stressed image is further decomposed into the primary component of strong edges and the smooth variation component. The image is, therefore, decomposed into primary, smooth and texture components. Coding schemes are developed for the three components; the primary component is encoded in intensity and geometric information, and the smooth and texture components are encoded using waveform coding techniques, leading to a hybrid of waveform coding and second generation coding techniques. The above hybrid system is of both high subjective and objective performance, especially at very low bit rates, and is further perceptually tuned for smooth and texture components based on the contrast-sensitivity of the HVS. This perceptually tuned hybrid system can be applied directly to components of color images and to the intra-coded frames in motion video sequences. The above image model has been generalized to a complex-valued 1-D case for an efficient representation of planar curves. Likewise, it can be generalized to a 3-D case for video coding and processing. We are also pursuing an approach for video coding based on the digital image warping techniques, in which the primary components of the three-component image models provide perceptually meaningful features for the specification of warping.

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Author information

Authors and Affiliations

  1. Electrical Engineering Department and Institute for Systems Research, University of Maryland, College Park, Maryland, 20742, USA

    Nariman Farvardin

  2. Systems Technology, Corporate Technology Group, National Semiconductor Corporation, 2900 Semiconductor Drive, Santa Clara, CA, 95052, USA

    Xiaonong Ran

Authors
  1. Nariman Farvardin
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  2. Xiaonong Ran
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Editor information

Editors and Affiliations

  1. Department of Signal Theory and Communications, Universitat Politècnica de Catalunya, 08034, Barcelona, Spain

    Luis Torres

  2. Signal Processing Laboratory, Swiss Federal Institute of Technology, 1015, Lausanne, Switzerland

    Murat Kunt

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© 1996 Kluwer Academic Publishers Boston

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Farvardin, N., Ran, X. (1996). A Perceptually Motivated Three-Component Image Model. In: Torres, L., Kunt, M. (eds) Video Coding. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1337-3_9

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  • DOI: https://doi.org/10.1007/978-1-4613-1337-3_9

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4612-8575-5

  • Online ISBN: 978-1-4613-1337-3

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