TY - GEN
T1 - Compressive sensing of object-signature
AU - Tamir, Dan E.
AU - Shaked, Natan T.
AU - Geerts, Wilhelmus J.
AU - Dolev, Shlomi
PY - 2011/7/29
Y1 - 2011/7/29
N2 - Compressive sensing is a new framework for signal acquisition, compression, and processing. Of specific interest are two-dimensional signals such as images where an optical unit performs the acquisition and compression (i.e., compressive sensing or compressive imaging). The signal reconstruction and processing can be done by optical signal processing and/or digital signal processing. In this paper we review the theoretical basis of compressive sensing, present an optical implementation of image acquisition, and introduce a new application of compressive sensing where the actual signals used in the compressive sensing process are image object-signature (an object-signature is a specific representation of an object). We detail the application of compressive sensing to image object-signature and show the potential of compressive sensing to compress the data through analysis of several methods for obtaining signature and evaluation of the rate/distortions results of different compression methods including compressive sensing applied to object-signature.
AB - Compressive sensing is a new framework for signal acquisition, compression, and processing. Of specific interest are two-dimensional signals such as images where an optical unit performs the acquisition and compression (i.e., compressive sensing or compressive imaging). The signal reconstruction and processing can be done by optical signal processing and/or digital signal processing. In this paper we review the theoretical basis of compressive sensing, present an optical implementation of image acquisition, and introduce a new application of compressive sensing where the actual signals used in the compressive sensing process are image object-signature (an object-signature is a specific representation of an object). We detail the application of compressive sensing to image object-signature and show the potential of compressive sensing to compress the data through analysis of several methods for obtaining signature and evaluation of the rate/distortions results of different compression methods including compressive sensing applied to object-signature.
KW - Compressive Imaging
KW - Compressive Sampling
KW - Compressive Sensing
KW - Digital Signal Processing
KW - Optical Super Computing
UR - http://www.scopus.com/inward/record.url?scp=79960737612&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-22494-2_8
DO - 10.1007/978-3-642-22494-2_8
M3 - Conference contribution
AN - SCOPUS:79960737612
SN - 9783642224935
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 63
EP - 77
BT - Optical Supercomputing - Third International Workshop, OSC 2010, Revised Selected Papers
T2 - 3rd International Workshop on Optical Supercomputing, OSC 2010
Y2 - 17 November 2010 through 19 November 2010
ER -