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Applied Sciences
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Advances on Image, Video and Signal Processing
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Advances on Image, Video and Signal Processing

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (20 July 2022) | Viewed by 3032

Special Issue Editors

Dr. Marco Castellani

E-Mail Website
Guest Editor
Department of Mechanical Engineering, University of Birmingham, Birmingham B15 2TT, UK
Interests: machine learning; swarm intelligence
Prof. Dr. Francesco Zirilli

E-Mail Website
Guest Editor
Dipartimento di Matematica “G. Castelnuovo”, Università di Roma “La Sapienza”, 00185 Roma, Italy
Interests: applied mathematics; mathematical modeling in physics and engineering; optimal control; optimization; inverse problems; mathematical finance; numerical methods
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue will consist of selected excellent papers from the 2022 4th International Conference on Image, Video and Signal Processing (IVSP 2022), which will be held in Singapore, on 18–20 March 2022. Contributors will be invited to submit and present papers in a wide variety of areas from concepts to applications. Topics of selected papers will include the latest research results and perspectives for future work in the image, video, and signal processing field. Related submissions outside the conference are also very welcome.

IVSP 2022 aims to provide researchers and practitioners from academia and industry with a forum to report on the latest developments in video, image, and signal processing, multimedia, and computer graphics.

This Special Issue is dedicated to demonstrating recent advances in the image, video, and signal processing field. Papers may report on original research, discuss methodological aspects, review the current state of the art, or offer perspectives on future prospects.

These papers will be subjected to peer review and are published so as to widely disseminate new research results, including developments and applications.

Topics of interest include but are not limited to:

  • Image processing;
  • Video processing;
  • Signal processing;
  • Speech processing;
  • Machine learning.

Dr. Marco Castellani
Prof. Dr. Francesco Zirilli
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 submissions that pass pre-check are 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. Applied Sciences 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 2400 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.

Published Papers (2 papers)

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Research

14 pages, 4555 KiB  
Article
An Efficient Method for Document Correction Based on Checkerboard Calibration Pattern
by Mina Ibrahim, Marian Wagdy, Fahd S. AlHarithi, Abdulrahman M. Qahtani, Wail S. Elkilani and Sameh Zarif
Appl. Sci. 2022, 12(18), 9014; https://doi.org/10.3390/app12189014 - 8 Sep 2022
Cited by 1 | Viewed by 1241
Abstract
Portable digital devices such as PDAs and camera phones are the easiest and most widely used methods to preserve and collect information. Capturing a document image using this method always has warping issues, especially when capturing pages from a book and rolled-up documents. [...] Read more.
Portable digital devices such as PDAs and camera phones are the easiest and most widely used methods to preserve and collect information. Capturing a document image using this method always has warping issues, especially when capturing pages from a book and rolled-up documents. In this article, we propose an effective method to correct the warping of the captured document image. The proposed method uses a checkerboard calibration pattern to calculate the world and image points. A radial distortion algorithm is used to handle the warping problem based on the computed image and world points. The proposed method obtained an error rate of 3% using a document de-warping dataset (CBDAR 2007). The proposed method achieved a high level of quality compared with other previous methods. Our method fixes the problem of warping in document images acquired with different levels of complexity, such as poor lighting, low quality, and different layouts. Full article
(This article belongs to the Special Issue Advances on Image, Video and Signal Processing)
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21 pages, 1406 KiB  
Article
A Novel Online Correlation Noise Model Based on Band Coefficients Mean to Achieve Low Computational and Coding-Efficient Distributed Video Codec
by Shahzad Khursheed, Nasreen Badruddin, Varun Jeoti and Manzoor Ahmed Hashmani
Appl. Sci. 2022, 12(13), 6505; https://doi.org/10.3390/app12136505 - 27 Jun 2022
Viewed by 1115
Abstract
Distributed video coding (DVC) is a novel coding paradigm that offers low computational encoding relative to conventional video-coding framework at the expense of high-decoding computational complexity. The challenging part of this video-coding framework is achieving better rate-distortion (RD) compared with conventional codec performance. [...] Read more.
Distributed video coding (DVC) is a novel coding paradigm that offers low computational encoding relative to conventional video-coding framework at the expense of high-decoding computational complexity. The challenging part of this video-coding framework is achieving better rate-distortion (RD) compared with conventional codec performance. A suitable and accurate correlation noise model (CNM) is crucial in improving the RD performance by achieving high coding efficiency and making decoding less computationally demanding. Since the correlation is nonstationary and time-variant and can vary from frame to frame, offline CNM estimation is not feasible for practical applications and real-time decoding. An online CNM may be the solution to this problem. In DVC, neither Wyner–Ziv frame (WZF) nor estimated side information (SI) of the corresponding WZF is available at the encoder. Therefore, online estimation of the CNM and its parameters can be quite challenging. The contribution of this research work is a novel online CNM which is computed by taking the mean of each transformed coefficient band and deployed for two different codecs. Our proposed codec, DIVCOM, which stands for “Distributed Video Coding with Online Band Mean Correlation Noise Model”, outperforms the existing baseline codec, DISCOVER (DIS), in both coding efficiency and peak signal-to-noise ratio (PSNR). The DIVCOM codec achieves coding efficiency of up to 8.05 kbps, and PSNR ranges from 0.0245 dB to 0.18 dB. An extended version of DIVCOM incorporating phase-based side information called PDIVCOM achieves coding efficiency up to 10.9 kbps, and PSNR ranges from 0.019 to 0.17 dB compared to DIS. Full article
(This article belongs to the Special Issue Advances on Image, Video and Signal Processing)
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