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Electronics
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Image and Video Quality and Compression
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Image and Video Quality and Compression

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 30 April 2024 | Viewed by 2373

Special Issue Editors

Dr. Xiaoming Li

E-Mail Website
Guest Editor
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore
Interests: image restoration and editing; GAN Priors; image inpainting and completion; face related tasks
Dr. Henghui Ding

E-Mail Website
Guest Editor
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore
Interests: scene understanding; multi-modal learning; low-shot learning; human–computer interaction

Special Issue Information

Dear Colleagues,

This Special Issue, entitled “Image and Video Quality and Compression” aims to explore the latest advancements and challenges in the field of visual media processing. This Special Issue will serve as a platform for researchers, experts, and practitioners to present their innovative research findings and methodologies in the domain of image and video quality assessment, compression algorithms, and perceptual optimization techniques.

This Special Issue will attend to a wide variety of topics, including objective and subjective quality assessment, advanced compression algorithms, adaptive streaming, low-latency video coding, and emerging technologies, such as 4K, 8K, and virtual reality. The primary focus of this Special Issue will be on developing efficient compression techniques that preserve a high visual quality while reducing file sizes and ensuring optimal playback experiences across various platforms and devices.

Researchers and practitioners are invited to submit their original work, including research papers, reviews, and case studies, to contribute to the advancement of image and video quality and compression. By collecting state-of-the-art research, this Special Issue will provide valuable insights and foster collaborations among experts in the field, facilitating the development of enhanced visual media applications and technologies.

Dr. Xiaoming Li
Dr. Henghui Ding
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. Electronics 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 (3 papers)

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Research

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22 pages, 30005 KiB  
Article
A Method for Generating Geometric Image Sequences for Non-Isomorphic 3D-Mesh Sequence Compression
by Yuan Gao, Zhiqiang Wang and Jin Wen
Electronics 2023, 12(16), 3473; https://doi.org/10.3390/electronics12163473 - 16 Aug 2023
Viewed by 756
Abstract
As virtual reality and 3D-modeling technology continue to advance, the amount of digital geometric media data is growing at an explosive rate. For example, 3D meshes, an important type of digital geometric media, can precisely record geometric information on a model’s surface. However, [...] Read more.
As virtual reality and 3D-modeling technology continue to advance, the amount of digital geometric media data is growing at an explosive rate. For example, 3D meshes, an important type of digital geometric media, can precisely record geometric information on a model’s surface. However, as the complexity and precision of 3D meshes increase, it becomes more challenging to store and transmit them. The traditional method of compressing non-isomorphic 3D-mesh sequences through frame-by-frame compression is inefficient and destroys the inter-frame correlations of the sequences. To tackle these issues, this study investigates the generation of time-dependent geometric image sequences for compressing non-isomorphic 3D-mesh sequences. Two methods are proposed for generating such sequences: one through image registration and the other through parametrization-geometry cooperative registration. Based on the experimental compression results of the video-coding algorithms, it was observed that the proposed geometric image-sequence-generation method offers superior objective and subjective qualities, as compared to the traditional method. Full article
(This article belongs to the Special Issue Image and Video Quality and Compression)
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15 pages, 679 KiB  
Article
A Fast Gradient Iterative Affine Motion Estimation Algorithm Based on Edge Detection for Versatile Video Coding
by Jingping Hong, Zhihong Dong, Xue Zhang, Nannan Song and Peng Cao
Electronics 2023, 12(16), 3414; https://doi.org/10.3390/electronics12163414 - 11 Aug 2023
Cited by 1 | Viewed by 796
Abstract
In the Versatile Video Coding (VVC) standard, affine motion models have been applied to enhance the resolution of complex motion patterns. However, due to the high computational complexity involved in affine motion estimation, real-time video processing applications face significant challenges. This paper focuses [...] Read more.
In the Versatile Video Coding (VVC) standard, affine motion models have been applied to enhance the resolution of complex motion patterns. However, due to the high computational complexity involved in affine motion estimation, real-time video processing applications face significant challenges. This paper focuses on optimizing affine motion estimation algorithms in the VVC environment and proposes a fast gradient iterative algorithm based on edge detection for efficient computation. Firstly, we establish judging conditions during the construction of affine motion candidate lists to streamline the redundant judging process. Secondly, we employ the Canny edge detection method for gradient assessment in the affine motion estimation process, thereby enhancing the iteration speed of affine motion vectors. The experimentalresults show that the encoding time of the affine motion estimation algorithm is about 15–35% lower than the overall encoding time of the anchor algorithm encoder, the average encoding time of the affine motion estimation part of the inter-frame prediction part is reduced by 24.79%, and the peak signal-to-noise ratio (PSNR) is only reduced by 0.04. Full article
(This article belongs to the Special Issue Image and Video Quality and Compression)
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Review

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14 pages, 4343 KiB  
Review
Review of Matrix Rank Constraint Model for Impulse Interference Image Inpainting
by Shuli Ma, Zhifei Li, Feihuang Chu, Shengliang Fang, Weichao Yang and Li Li
Electronics 2024, 13(3), 470; https://doi.org/10.3390/electronics13030470 - 23 Jan 2024
Viewed by 473
Abstract
Camera failure or loss of storage components in imaging equipment may result in the loss of important image information or random pulse noise interference. The low-rank prior is one of the most important priors in image optimization processing. This paper reviews and compares [...] Read more.
Camera failure or loss of storage components in imaging equipment may result in the loss of important image information or random pulse noise interference. The low-rank prior is one of the most important priors in image optimization processing. This paper reviews and compares some low-rank constraint models for image matrices. Firstly, an overview of image-inpainting models based on nuclear norm, truncated nuclear norm, weighted nuclear norm, and matrix-factorization-based F norm is presented, and corresponding optimization iterative algorithms are provided. Then, we use different image matrix low-order constraint models to recover satellite images from three types of pulse interference and provide our experimental visual and numerical results. Finally, it can be concluded that the method based on the weighted nuclear norm can achieve the best image restoration effect. The F norm method based on matrix factorization has the shortest computational time and can be used for large-scale low-rank matrix calculations. Compared with nuclear norm-based methods, weighted nuclear norm-based methods and truncated nuclear norm-based methods can significantly improve repair performance. Full article
(This article belongs to the Special Issue Image and Video Quality and Compression)
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