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Title

Compressive Imaging using RIP-compliant CMOS Imager Architecture and Landweber Reconstruction

AuthorsTrevisi, Marco; Akbari, Ali; Trocan, María; Rodríguez-Vázquez, Ángel ; Carmona-Galán, R.
KeywordsCMOS image sensor architecture
Compressive sensing
Landweber reconstruction
Power spectral density
Random binary matrix RIP proof
Single value decomposition
Ternary measurement matrix
Issue Date2020
PublisherInstitute of Electrical and Electronics Engineers
CitationIEEE Transactions on Circuits and Systems for Video Technology, 30(2): 387-399 (2020)
AbstractIn this paper, we present a new image sensor architecture for fast and accurate compressive sensing (CS) of natural images. Measurement matrices usually employed in CS CMOS image sensors are recursive pseudo-random binary matrices. We have proved that the restricted isometry property of these matrices is limited by a low sparsity constant. The quality of these matrices is also affected by the non-idealities of pseudo-random number generators (PRNG). To overcome these limitations, we propose a hardware-friendly pseudo-random ternary measurement matrix generated on-chip by means of class III elementary cellular automata (ECA). These ECA present a chaotic behavior that emulates random CS measurement matrices better than other PRNG. We have combined this new architecture with a block-based CS smoothed-projected Landweber reconstruction algorithm. By means of single value decomposition, we have adapted this algorithm to perform fast and precise reconstruction while operating with binary and ternary matrices. Simulations are provided to qualify the approach
Publisher version (URL)https://doi.org/10.1109/TCSVT.2019.2892178
URIhttp://hdl.handle.net/10261/227345
DOI10.1109/TCSVT.2019.2892178
Appears in Collections:(IMSE-CNM) Artículos
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