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Special Issue "Video Coding Based on Compressive Sensing"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: 15 June 2022.

Special Issue Editors

Dr. Evgeny Belyaev
E-Mail Website
Guest Editor
ITMO University, Kronverksky prospekt 49, 197101, Saint-Petersburg, Russia
Interests: video coding and transmission; arithmetic coding; compressive sensing
Prof. Dr. Karen Egiazarian
E-Mail Website
Guest Editor
Tampere University; Korkeakoulunkatu 1, 33720 Tampere, Finland
Interests: computational imaging; compressed sensing; efficient signal processing algorithms; image/video restoration and compression
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

According to compressive sensing (CS) frameworks, if a signal is sparse in some transform domain, then it can be recovered from a much smaller number of samples than the Nyquist–Shannon theorem requires. This enables potentially wide opportunities in the development of new cheap sensors, including tiny video encoding devices. Potentially, CS-based video coding methods have the following advantages. First, at the encoder side, it could be enough to perform a linear transformation, select a few coefficients located at pseudo-random positions (called measurements), and send them to the decoder. A computational complexity of such operation could be comparable to JPEG encoding complexity. Second, the measurements could be coded and transmitted independently from each other. As a result, a large number of bit stream scalability layers can be supported, and loss of some measurements (due to packet losses in a communication channel) does not affect other delivered measurements which can be used for decoding without an error propagation effect. However, existing video codecs based on CS are significantly inferior in terms of rate-distortion performance to conventional codecs, such as H.264/AVC or H.265/HEVC. Moreover, CS recovery algorithms require relatively high computational complexity, which makes it difficult to perform them in real-time. This Special Issue is addressed at the new approaches which help to overcome the above- listed limitations of the existing CS video codecs.

Dr. Evgeny Belyaev 
Prof. Dr. Karen Egiazarian
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • compressive sensing
  • video coding
  • sparse recovery
  • entropy coding
  • video streaming

Published Papers

This special issue is now open for submission.
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