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Modeling human-like intelligent image processing: An information processing perspective and approach
Affiliation:1. Key Laboratory of Ministry of Education for Advanced Display and System Application, Shanghai University, Shanghai 200072, China;2. School of Communication and Information Engineering, Shanghai University, Shanghai 200072, China;1. Shaanxi Key Lab of Speech & Image Information Processing (SAIIP), School of Computer Science, Northwestern Polytechnical University, Xi׳an 710072, China;2. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
Abstract:We live in the Information Age, and information has become a critically important component of our life. The success of the Internet made huge amounts of it easily available and accessible to everyone. To keep the flow of this information manageable, means for its faultless circulation and effective handling have become urgently required. Considerable research efforts are dedicated today to address this necessity, but they are seriously hampered by the lack of a common agreement about “What is information?” In particular, what is “visual information”—human's primary input from the surrounding world. The problem is further aggravated by a long-lasting stance borrowed from the biological vision research that assumes human-like information processing as an enigmatic mix of perceptual and cognitive vision faculties. I am trying to find a remedy for this bizarre situation. Relying on a new definition of “information”, which can be derived from Kolmogorov's complexity theory and Chaitin's notion of algorithmic information, I propose a unifying framework for visual information processing, which explicitly accounts for the perceptual and cognitive image processing peculiarities. I believe that this framework will be useful to overcome the difficulties that are impeding our attempts to develop the right model of human-like intelligent image processing.
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