Literature DB >> 20357845

Compressive video sensors using multichannel imagers.

Mohan Shankar1, Nikos P Pitsianis, David J Brady.   

Abstract

We explore the possibilities of obtaining compression in video through modified sampling strategies using multichannel imaging systems. The redundancies in video streams are exploited through compressive sampling schemes to achieve low power and low complexity video sensors. The sampling strategies as well as the associated reconstruction algorithms are discussed. These compressive sampling schemes could be implemented in the focal plane readout hardware resulting in drastic reduction in data bandwidth and computational complexity.

Year:  2010        PMID: 20357845     DOI: 10.1364/AO.49.0000B9

Source DB:  PubMed          Journal:  Appl Opt        ISSN: 1559-128X            Impact factor:   1.980


  2 in total

1.  Nonparametric Bayesian dictionary learning for analysis of noisy and incomplete images.

Authors:  Mingyuan Zhou; Haojun Chen; John Paisley; Lu Ren; Lingbo Li; Zhengming Xing; David Dunson; Guillermo Sapiro; Lawrence Carin
Journal:  IEEE Trans Image Process       Date:  2011-06-20       Impact factor: 10.856

2.  A Dual-Mode 303-Megaframes-per-Second Charge-Domain Time-Compressive Computational CMOS Image Sensor.

Authors:  Keiichiro Kagawa; Masaya Horio; Anh Ngoc Pham; Thoriq Ibrahim; Shin-Ichiro Okihara; Tatsuki Furuhashi; Taishi Takasawa; Keita Yasutomi; Shoji Kawahito; Hajime Nagahara
Journal:  Sensors (Basel)       Date:  2022-03-02       Impact factor: 3.576

  2 in total

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