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Noise performance of non-iterative compressed sensing based recovery algorithm: surveillance applications

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Abstract

Compressed sensing has been of great interest in signal compression since it promises higher compression level and ease in usage. It is widely used in signal processing domain for compression and reconstruction of various signals including electrical signals, images, videos, etc. The concept of compressed sensing can be applied suitably for surveillance videos since voluminous video quantities can be significantly compressed and retrieved perfectly. The surveillance videos are prone to various noises like impulse noise, quantization noise, multiplicative noise, etc., that raise as hindrance to high quality video reconstruction. Thus, non-iterative compressed sensing based recovery algorithm is proposed that recovers the surveillance videos with higher perfection in the presence of various noises. The algorithm uses augmented matrix as sensing matrix and hence avoids iterations leading to commendable reduction in runtime. The signal to noise ratio obtained using the proposed algorithm is ~39 dB which is greater than any other existing noise removing CS recovery algorithms like OMP-CV, TMSBL, etc. High speed recovery is made possible due to the absence of iterations. Accuracy and structural similarity obtained are nearly 98% and 95% respectively. The algorithm is robust to various noise levels and the hardware implementation shows that the algorithm is simple enough to be used in hardware of lower specifications. These results ensure NIPIRA as a best suitor for real time surveillance video reconstruction even in the presence of noise.

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Authors and Affiliations

  1. Department of Electronics and Communications Engineering, Sri Sivasubramaniya Nadar College of Engineering, Kalavakkam, Old Mahabalipuram Road, Chennai, Tamilnadu, 603110, India

    J. Florence Gnana Poovathy &  S. Radha

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  1. J. Florence Gnana Poovathy
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  2. S. Radha
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Correspondence to J. Florence Gnana Poovathy.

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J. Florence Gnana Poovathy, S. Radha Noise performance of non-iterative compressed sensing based recovery algorithm: surveillance applications. Multimed Tools Appl 77, 7595–7613 (2018). https://doi.org/10.1007/s11042-017-4662-5

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  • DOI: https://doi.org/10.1007/s11042-017-4662-5

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