Special Issue "Recent Advances in Video Compression and Coding"

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Processes".

Deadline for manuscript submissions: 20 January 2022.

Special Issue Editors

Dr. Zhaoqing Pan
E-Mail Website
Guest Editor
School of Electrical and Information Engineering, Tianjin University, Tianjin, China
Interests: multimedia processing; video coding/compression
Dr. Yuan Tian
E-Mail Website
Co-Guest Editor
School of Computer Engineering, Nanjing Institute of Technology, Nanjing 210000, China
Interests: blockchain; big data; smart grids; privacy; security
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the development of imaging and display technologies, high definition video has become more and more popular in our lifetime. However, with the increased quality of resolution, frame rate, sampling precision, etc., the volume of raw video data has increased significantly. The huge amount of raw video data is a challenge for signal processing, storage, and transmitting. Hence, efficient video compression coding technology becomes vitally important for the video to be widely used in multimedia applications.

Video compression is a practical implementation of source coding in information theory. It fits the scopes and the developing trends of the journal Information very well. This Special Issue focuses on the theoretical and practical design issues of video compression and coding. Our aim is to bring together researchers, industry practitioners, and individuals working on the related areas to share their new ideas, latest findings, and state-of-the-art achievements with others.

The topics of interest include, but are not limited to:

  • Low-complexity video coding
  • Optimization algorithms for video coding
  • Transform optimization algorithms for video coding
  • Transcoding algorithms
  • Video object detection algorithms
  • Coding algorithms for 3D/HDR/ videos
  • Video information hiding algorithms
  • Video broadcasting system
  • Advanced algorithms for video watermarking
  • Artificial intelligence for video processing

Dr. Zhaoqing Pan
Dr. Yuan Tian
Guest Editor

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. Information is an international peer-reviewed open access monthly 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 1400 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

  • multimedia processing
  • video compression
  • video coding
  • video transcoding

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Article
Joint Subtitle Extraction and Frame Inpainting for Videos with Burned-In Subtitles
Information 2021, 12(6), 233; https://doi.org/10.3390/info12060233 - 29 May 2021
Viewed by 972
Abstract
Subtitles are crucial for video content understanding. However, a large amount of videos have only burned-in, hardcoded subtitles that prevent video re-editing, translation, etc. In this paper, we construct a deep-learning-based system for the inverse conversion of a burned-in subtitle video to a [...] Read more.
Subtitles are crucial for video content understanding. However, a large amount of videos have only burned-in, hardcoded subtitles that prevent video re-editing, translation, etc. In this paper, we construct a deep-learning-based system for the inverse conversion of a burned-in subtitle video to a subtitle file and an inpainted video, by coupling three deep neural networks (CTPN, CRNN, and EdgeConnect). We evaluated the performance of the proposed method and found that the deep learning method achieved high-precision separation of the subtitles and video frames and significantly improved the video inpainting results compared to the existing methods. This research fills a gap in the application of deep learning to burned-in subtitle video reconstruction and is expected to be widely applied in the reconstruction and re-editing of videos with subtitles, advertisements, logos, and other occlusions. Full article
(This article belongs to the Special Issue Recent Advances in Video Compression and Coding)
Show Figures

Figure 1

Back to TopTop