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Object‐oriented image analysis for very‐low‐bitrate video‐coding systems using the CNN universal machine
Author(s) -
Stoffels André,
Roska Tamás,
Chua Leon O.
Publication year - 1997
Publication title -
international journal of circuit theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 52
eISSN - 1097-007X
pISSN - 0098-9886
DOI - 10.1002/(sici)1097-007x(199707/08)25:4<235::aid-cta961>3.0.co;2-q
Subject(s) - computer science , coding (social sciences) , joins , computer engineering , theoretical computer science , artificial intelligence , data compression , computer vision , computer graphics (images) , mathematics , programming language , statistics
The CNN universal machine (CNNUM) is applied to object‐oriented video compression and proves its universality for future applications in the field of very‐low‐bitrate coding. This proposal joins recent work of Venetianer and Roska in unfolding the enormous computational abilities of the CNNUM for a wide class of video compression techniques. Here a novel image analysis technique is considered and realized in the form of analogic CNN algorithms. The specific features of the scheme, among them the extensive use of dynamic (finite running time) CNN cloning templates, are outlined and discussed through different computer simulations. When implemented on the CNNUM, its performances outdo those of equivalent digital systems and qualify the CNNUM as a serious competitor for future video coding hardware. © 1997 John Wiley & Sons, Ltd.