A Survey and Theoretical View on Compressive Sensing and Reconstruction
Author(s) -
Santosh S. Bujari,
Saroja V. Siddamal
Publication year - 2016
Publication title -
international journal of image graphics and signal processing
Language(s) - English
Resource type - Journals
eISSN - 2074-9082
pISSN - 2074-9074
DOI - 10.5815/ijigsp.2016.04.01
Subject(s) - compressed sensing , nyquist rate , computer science , nyquist–shannon sampling theorem , bandwidth (computing) , analog signal , signal reconstruction , signal (programming language) , encoder , data acquisition , electronic engineering , signal processing , sampling (signal processing) , digital signal processing , telecommunications , algorithm , computer hardware , computer vision , engineering , operating system , detector , programming language
Most of the current embedded systems operate on digital domain even though input and output is analog in nature. All these devices contain ADC (Analog to Digital converter) to convert the analog signal in to digital domain which is used for processing as per the application. Images, videos and other data can be exactly recovered from a set of uniformly spaced samples taken at the Nyquist rate. Due to the recent technology signal bandwidth is becoming wider and wider. To meet the higher demand, signal acquisition system need to be improved. Traditional Nyquist rate which is used in signal acquisition suggests taking more numbers of samples to increase the bandwidth but while reconstruction most of the samples are not used. If samples are as per Nyquist rate then, this increases the complexity of encoder, storage of samples and signal processing. To avoid this new concept Compressive Sensing is used as an alternative for traditional sampling theory. This paper presents a survey and simplified theoretical view on compressive sensing and reconstruction and proposed work is introduced.
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