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Electronics
Special Issues
Multimedia Processing: Challenges and Prospects
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Multimedia Processing: Challenges and Prospects

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

Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 15506

Special Issue Editors

Prof. Dr. Zhaoqing Pan

E-Mail Website
Guest Editor
School of Electrical and Information Engineering, Tianjin University, Tianjin 300350, China
Interests: multimedia processing; video coding/compression
Prof. Dr. Yang Xiao

E-Mail Website
Guest Editor
Department of Computer Science, The University of Alabama, Tuscaloosa, AL 35487, USA
Interests: cyber-physical systems; Internet of Things; Multimedia Processing; security and telemedicine
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Mohammad Mehedi Hassan

E-Mail Website
Guest Editor
College of Computer and Information Sciences, King Saud University, Riyadh 11543, Saudi Arabia
Interests: multimedia processing; cloud/edge computing; internet of things; artificial intelligence
Dr. Yuan Tian

E-Mail Website
Guest Editor
1. School of International Education, Nanjing Institute of Technology, Nanjing 211167, China
2. Waterford Institute, Nanjing University of Information Science and Technology, Nanjing 211800, China
Interests: cyber security; applied cryptography; multimedia security; privacy protection; biometrics; security management; location based service; cloud computing security
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the rapid development of information technology, multimedia data such as image and video has been widely used in our daily life. Before these multimedia data can be used for multimedia devices, they need to be processed. For example, the raw image/video should be compressed before transiting, while the visual quality of compressed image/video is degraded. In order to increase the visual quality of compressed multimedia data, the quality enhancement operation should be performed. Hence, the multimedia processing methods are quite important for multimedia data application.

Moreover, with the development of internet technology, multimedia data has been widely adopted in multimedia devices, such as video surveillance, webcast, and so on. For multimedia data security, the sensitive multimedia data needs to be protected before transmission. Data encryption is an efficient way to achieve this purpose. Compared with the text and binary data, the multimedia data has huge volume, and requires real-time processing, hence, the efficient video encryption algorithms should be designed for multimedia data security.

This Special Issue in Electronics focuses on the theoretical and practical design issues of multimedia data processing. 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. This will provide readers with a clear understanding of the recent achievements on multimedia data processing.

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

  • Advanced algorithm for multimedia data compression
  • Advanced algorithm for multimedia quality enhancement
  • Advanced algorithm for multimedia data quality assessment
  • Advanced image/video super-resolution algorithms
  • Advanced algorithm for image/video analysis and segmentation
  • Advanced algorithm for image/video Interpretation and understanding
  • Advanced algorithm for image/video detection, recognition, and classification
  • Advanced algorithm for image/video labeling and retrieval
  • Advanced multimedia data transmission security algorithms
  • Advanced multimedia data hiding algorithms
  • Advanced threat detection algorithms for multimedia broadcasting system
  • Advanced algorithms for multimedia authentication and encryption
  • Advanced algorithms for multimedia data copyright protection
  • Advanced algorithms for multimedia data watermarking
  • Advanced multimedia data privacy protection algorithms
  • Artificial intelligence for multimedia data processing

Dr. Zhaoqing Pan
Prof. Dr. Yang Xiao
Prof. Dr. Mohammad Mehedi Hassan
Dr. Yuan Tian
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.

Keywords

  • Multimedia Processing
  • Multimedia Security

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Published Papers (6 papers)

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Research

18 pages, 7717 KiB  
Article
Hiding and Extracting Important Information in Encrypted Images by Using the Transformation of All Possible Permutations and VQ Codebook
by Heng-Xiao Chi, Chin-Chen Chang, Xu Wang and Chia-Chen Lin
Electronics 2022, 11(21), 3475; https://doi.org/10.3390/electronics11213475 - 26 Oct 2022
Cited by 5 | Viewed by 1531
Abstract
Due to its applications in cloud computing, research on reversible data hiding in encrypted images (RDHEI) is becoming more and more important. This paper proposes a reversible data hiding scheme for encrypted images that utilizes an all-permutation technique to embed data into encrypted [...] Read more.
Due to its applications in cloud computing, research on reversible data hiding in encrypted images (RDHEI) is becoming more and more important. This paper proposes a reversible data hiding scheme for encrypted images that utilizes an all-permutation technique to embed data into encrypted images. The proposed scheme follows a block-wise data hiding process. Message extraction and image restoration are performed by the receiver using the trained vector quantization (VQ) codebook. This scheme can provide a high embedding rate and reduce the hardware burden on the receiver. Full article
(This article belongs to the Special Issue Multimedia Processing: Challenges and Prospects)
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24 pages, 241265 KiB  
Article
Novel Hybrid Fusion-Based Technique for Securing Medical Images
by Hanaa A. Abdallah, Reem Alkanhel and Abdelhamied A. Ateya
Electronics 2022, 11(20), 3421; https://doi.org/10.3390/electronics11203421 - 21 Oct 2022
Cited by 1 | Viewed by 1951
Abstract
The security of images has gained great interest in modern communication systems. This is due to the massive critical applications that are based on images. Medical imaging is at the top of these applications. However, the rising number of heterogenous attacks push toward [...] Read more.
The security of images has gained great interest in modern communication systems. This is due to the massive critical applications that are based on images. Medical imaging is at the top of these applications. However, the rising number of heterogenous attacks push toward the development of securing algorithms and methods for imaging systems. To this end, this work considers developing a novel authentication, intellectual property protection, ownership, and security technique for imaging systems, mainly for medical imaging. The developed algorithm includes two security modules for safeguarding various picture kinds. The first unit is accomplished by applying watermarking authentication in the frequency domain. The singular value decomposition (SVD) is performed for the host image’s discrete cosine transform (DCT) coefficients. The singular values (S) are divided into 64 × 64 non-overlapping blocks, followed by embedding the watermark in each block to be robust to any attack. The second unit is made up of two encryption layers to provide double-layer security to the watermarked image. The double random phase encryption (DRPE) and chaotic encryption have been tested and examined in the encryption unit. The suggested approach is resistant to common image processing attacks, including rotation, cropping, and adding Gaussian noise, according to the findings of the experiments. The encryption of watermarked images in the spatial and DCT domains and fused watermarked images in the DCT domain are all discussed. The transparency and security of the method are assessed using various measurements. The proposed approach achieves high-quality reconstructed watermarks and high security by using encryption to images and achieves robustness against any obstructive attacks. The developed hybrid algorithm recovers the watermark even in the presence of an attack with a correlation near 0.8. Full article
(This article belongs to the Special Issue Multimedia Processing: Challenges and Prospects)
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17 pages, 2356 KiB  
Article
Key Information Extraction and Talk Pattern Analysis Based on Big Data Technology: A Case Study on YiXi Talks
by Hao Xu, Chengzhi Jiang, Chuanfeng Huang, Yiyang Chen, Mengxue Yi and Zhentao Zhu
Electronics 2022, 11(4), 640; https://doi.org/10.3390/electronics11040640 - 18 Feb 2022
Cited by 7 | Viewed by 1926
Abstract
In the attempt to extract key information and talk patterns from YiXi talks in China to realize “strategic reading” for readers and newcomers of the speaking field, text mining methods are used by this work. The extraction of key information is realized by [...] Read more.
In the attempt to extract key information and talk patterns from YiXi talks in China to realize “strategic reading” for readers and newcomers of the speaking field, text mining methods are used by this work. The extraction of key information is realized by keyword extraction using the TF-IDF algorithm to show key information of one talk or one category of talks. Talk pattern recognition is realized by manual labeling (100 transcripts) and rule-based automatic programs (590 transcripts). The labeling accuracy rate of “main narrative angle” recognition is the highest (70.34%), followed by “opening form” (65.25%) and “main narrative object”, and the “ending form” is around 50%, with the overall accuracy of the rule-based automatic recognition program for talk patterns at approximately 60%. The obtained results show that the proposed keyword extraction technology for transcripts can provide “strategic reading” to a certain extent. Mature speech mode can be summarized as follows: speakers tend to adopt a self-introducing opening format. They tell stories and experiences through a first-person narrative angle and express expectations and prospects for the future. This pattern is reasonable and can be referenced by new speakers. Full article
(This article belongs to the Special Issue Multimedia Processing: Challenges and Prospects)
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11 pages, 13253 KiB  
Article
Infrared Image Super-Resolution via Progressive Compact Distillation Network
by Kefeng Fan, Kai Hong and Fei Li
Electronics 2021, 10(24), 3107; https://doi.org/10.3390/electronics10243107 - 14 Dec 2021
Cited by 5 | Viewed by 3160
Abstract
Deep convolutional neural networks are capable of achieving remarkable performance in single-image super-resolution (SISR). However, due to the weak availability of infrared images, heavy network architectures for insufficient infrared images are confronted by excessive parameters and computational complexity. To address these issues, we [...] Read more.
Deep convolutional neural networks are capable of achieving remarkable performance in single-image super-resolution (SISR). However, due to the weak availability of infrared images, heavy network architectures for insufficient infrared images are confronted by excessive parameters and computational complexity. To address these issues, we propose a lightweight progressive compact distillation network (PCDN) with a transfer learning strategy to achieve infrared image super-resolution reconstruction with a few samples. We design a progressive feature residual distillation (PFDB) block to efficiently refine hierarchical features, and parallel dilation convolutions are utilized to expand PFDB’s receptive field, thereby maximizing the characterization power of marginal features and minimizing the network parameters. Moreover, the bil-global connection mechanism and the difference calculation algorithm between two adjacent PFDBs are proposed to accelerate the network convergence and extract the high-frequency information, respectively. Furthermore, we introduce transfer learning to fine-tune network weights with few-shot infrared images to obtain infrared image mapping information. Experimental results suggest the effectiveness and superiority of the proposed framework with low computational load in infrared image super-resolution. Notably, our PCDN outperforms existing methods on two public datasets for both ×2 and ×4 with parameters less than 240 k, proving its efficient and excellent reconstruction performance. Full article
(This article belongs to the Special Issue Multimedia Processing: Challenges and Prospects)
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13 pages, 868 KiB  
Article
Ciphertext-Policy Attribute-Based Encryption with Outsourced Set Intersection in Multimedia Cloud Computing
by Yanfeng Shi and Shuo Qiu
Electronics 2021, 10(21), 2685; https://doi.org/10.3390/electronics10212685 - 3 Nov 2021
Cited by 3 | Viewed by 1898
Abstract
In a multimedia cloud computing system, suppose all cloud users outsource their own data sets to the cloud in the encrypted form. Each outsourced set is associated with an access structure such that a valid data user, Bob, with the credentials satisfying the [...] Read more.
In a multimedia cloud computing system, suppose all cloud users outsource their own data sets to the cloud in the encrypted form. Each outsourced set is associated with an access structure such that a valid data user, Bob, with the credentials satisfying the access structure is able to conduct computing over outsourced encrypted set (e.g., decryption or other kinds of computing function). Suppose Bob needs to compute the set intersection over a data owner Alice’s and his own outsourced encrypted sets. Bob’s simple solution is to download Alice’s and Bob’s outsourced encrypted sets, perform set intersection operation, and decrypt the set intersection ciphertexts. A better solution is for Bob to delegate the cloud to calculate the set intersection, without giving the cloud any ability in breaching the secrecy of the sets. To solve this problem, this work introduces a novel primitive called ciphertext-policy attribute-based encryption with outsourced set intersection for multimedia cloud computing. It is the first cryptographic algorithm supporting a fully outsourced encrypted storage, computation delegation, fine-grained authorization security for ciphertext-policy model, without relying on an online trusted authority or data owners, and multi-elements set, simultaneously. We construct a scheme that provably satisfies the desirable security properties, and analyze its efficiency. Full article
(This article belongs to the Special Issue Multimedia Processing: Challenges and Prospects)
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10 pages, 2449 KiB  
Article
Solar Active Region Detection Using Deep Learning
by Lin Quan, Long Xu, Ling Li, Huaning Wang and Xin Huang
Electronics 2021, 10(18), 2284; https://doi.org/10.3390/electronics10182284 - 17 Sep 2021
Cited by 6 | Viewed by 3265
Abstract
Solar eruptive events could affect radio communication, global positioning systems, and some high-tech equipment in space. Active regions on the Sun are the main source regions of solar eruptive events. Therefore, the automatic detection of active regions is important not only for routine [...] Read more.
Solar eruptive events could affect radio communication, global positioning systems, and some high-tech equipment in space. Active regions on the Sun are the main source regions of solar eruptive events. Therefore, the automatic detection of active regions is important not only for routine observation, but also for the solar activity forecast. At present, active regions are manually or automatically extracted by using traditional image processing techniques. Because active regions dynamically evolve, it is not easy to design a suitable feature extractor. In this paper, we first overview the commonly used methods for active region detection currently. Then, two representative object detection models, faster R-CNN and YOLO V3, are employed to learn the characteristics of active regions, and finally establish a deep learning–based detection model of active regions. The performance evaluation demonstrates that the high accuracy of active region detection is achieved by both the two models. In addition, YOLO V3 is 4% and 1% better than faster R-CNN in terms of true positive (TP) and true negative (TN) indexes, respectively; meanwhile, the former is eight times faster than the latter. Full article
(This article belongs to the Special Issue Multimedia Processing: Challenges and Prospects)
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