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14 October 2003 Localized linear operators: application to image sequence compression using optical signal processing
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Proceedings Volume 5062, Smart Materials, Structures, and Systems; (2003) https://doi.org/10.1117/12.514761
Event: Smart Materials, Structures, and Systems, 2002, Bangalore, India
Abstract
This paper discusses about the extension of Gabor Expansions to the optical domain and the design of an efficient filter bank to provide adaptive equalization in the light of Optical Signal Processing. The isomorphism between this localized linear operator and the filter design fundamentals are examined in the framework of image sequence compression. A new and efficient technique to perform Gabor expansion of Optical signals is introduced. The multi-resolution representation of data is considered in particular. A new approach to filter bank design in optical domain, using matrix formulation is introduced. Using this approach, an efficient optical filter bank with low complexity and good frequency response is designed. It is interesting to note that this design is a mathematical model of the quincunx filter bank. The characteristics of this optical filter bank are compared with that of other commonly used short kernel filter banks, for video compression applications. The approach is based on multi-resolution representation of data, which is generated by the filter bank proposed in this work. The use of multi-resolution data structure in conjunction with other components of the system allows a simple and efficient implementation. Simulations on typical image sequences show that it is possible to perform generic coding with reduced complexity and good efficiency.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dipnarayan Guha "Localized linear operators: application to image sequence compression using optical signal processing", Proc. SPIE 5062, Smart Materials, Structures, and Systems, (14 October 2003); https://doi.org/10.1117/12.514761
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