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Adaptive block compressed sensing - a technological analysis and survey on challenges, innovation directions and applications

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Abstract

In today’s digital world, data transmission and storage is becoming a massive problem. This is because the data produced by various sensors worldwide is outstripping the ability to store them. Pre-processing the entire data before transmission is the best solution for reducing the storage issue. ‘Compressed sensing’(CS) is a pre-processing technique that exploits the sparsity of the signal for sampling the data. Since most of the natural signals are sparse, CS allows sampling at a rate lesser than that required in Nyquist sampling theorem. However, in conventional CS, sampling is done for the entire image at once which increases processing time and reduces visual quality. In block compressed sensing (BCS), blocks of the images are processed simultaneously which increases processing speed and decreases the processing time. To improve the quality of the reconstructed signal, a variant of BCS, Adaptive block compressed sensing (ABCS) is used. This review paper studies the advantages, challenges and applications of applying ABCS for image compression.

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Authors and Affiliations

  1. Department of ECE, College of Engineering and Technology, Faculty of Engineering and Technology, SRM institute of Science and Technology, SRM Nagar, Kattankulathur 603203, Chengalpattu District, Tamilnadu, India

    R. Monika, Dhanalakshmi Samiappan & R. Kumar

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  1. R. Monika
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  2. Dhanalakshmi Samiappan
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  3. R. Kumar
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Correspondence to Dhanalakshmi Samiappan.

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Monika, R., Samiappan, D. & Kumar, R. Adaptive block compressed sensing - a technological analysis and survey on challenges, innovation directions and applications. Multimed Tools Appl 80, 4751–4768 (2021). https://doi.org/10.1007/s11042-020-09932-0

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  • DOI: https://doi.org/10.1007/s11042-020-09932-0

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