DocumentCode
3339152
Title
The simplest measurement matrix for compressed sensing of natural images
Author
He, Zaixing ; Ogawa, Takahiro ; Haseyama, Miki
Author_Institution
Grad. Sch. of Inf. Sci. & Technol., Hokkaido Univ., Sapporo, Japan
fYear
2010
fDate
26-29 Sept. 2010
Firstpage
4301
Lastpage
4304
Abstract
There exist two main problems in currently existing measurement matrices for compressed sensing of natural images, the difficulty of hardware implementation and low sensing efficiency. In this paper, we present a novel simple and efficient measurement matrix, Binary Permuted Block Diagonal (BPBD) matrix. The BPBD matrix is binary and highly sparse (all but one or several “1”s in each column are “0”s). Therefore, it can simplify the compressed sensing procedure dramatically. The proposed measurement matrix has the following advantages, which cannot be entirely satisfied by existing measurement matrices. (1) It has easy hardware implementation because of the binary elements; (2) It has high sensing efficiency because of the highly sparse structure; (3) It is incoherent with different popular sparsity basis´ like wavelet basis and gradient basis; (4) It provides fast and nearly optimal reconstructions. Moreover, the simulation results demonstrate the advantages of the proposed measurement matrix.
Keywords
image coding; matrix algebra; natural scenes; BPBD matrix; binary elements; binary permuted block diagonal matrix; compressed sensing procedure; gradient basis; hardware implementation; high sensing efficiency; highly sparse structure; low sensing efficiency; measurement matrices; natural images; optimal reconstructions; popular sparsity basis; simplest measurement matrix; wavelet basis; Coherence; Compressed sensing; Hardware; Image reconstruction; Minimization; Sensors; Sparse matrices; Compressed sensing; binary permuted block diagonal matrix; hardware implementation; sensing efficiency;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing (ICIP), 2010 17th IEEE International Conference on
Conference_Location
Hong Kong
ISSN
1522-4880
Print_ISBN
978-1-4244-7992-4
Electronic_ISBN
1522-4880
Type
conf
DOI
10.1109/ICIP.2010.5651800
Filename
5651800
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