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Electronics
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New Techniques for Image and Video Coding
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New Techniques for Image and Video Coding

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

Deadline for manuscript submissions: closed (31 May 2022) | Viewed by 8834

Special Issue Editor

Prof. Dr. Otoniel Mario López Granado

E-Mail Website
Guest Editor
Department of Physics and Computer Architecture, Miguel Hernández University, 03205 Elche, Spain
Interests: image compression; video coding; parallel computing; multimedia transmission

Special Issue Information

Dear Colleagues,

As reported by the Cisco Visual Networking Index (2017–22), IP video traffic represented 73% of the total IP traffic in 2016 and is expected to reach 82% by 2022. This means that a million minutes of video content travels through the network every second. The report also predicts a great increase in services such as Video on Demand (VoD), Live Internet video, as well as Virtual Reality (VR) and Augmented Reality (AR). Due to the increasing number of consumers (4.8 billion internet users by 2022) and greater video resolution (4K and 8K), VoD traffic will double by 2022. There is also intense interest in the live video streaming of sports events, where 4K- and 5K-resolution cameras (more than 20) are installed around a stadium to transmit a 360° view of these events.

To address this increase in video IP traffic, a new generation of image compression and video coding techniques are required to achieve higher compression rates than the ones obtained by the previous image and video coding standards.

This Special Issue is intended to provide a forum for recent research in both image compression and video coding techniques that would have potential to further improve the performance of current image/video coding standards.

Prof. Dr. Otoniel Mario López Granado
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 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

  • High efficiency coding techniques
  • Perceptual coding
  • Parallel video coding techniques (multicore, GPU)
  • Hardware video coding accelerators (FPGA, DSP)

Published Papers (4 papers)

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Research

12 pages, 6244 KiB  
Article
An Effective Multi-Task Two-Stage Network with the Cross-Scale Training Strategy for Multi-Scale Image Super Resolution
by Jucheng Yang, Feng Wei, Yaxin Bai, Meiran Zuo, Xiao Sun and Yarui Chen
Electronics 2021, 10(19), 2434; https://doi.org/10.3390/electronics10192434 - 07 Oct 2021
Cited by 3 | Viewed by 1610
Abstract
Convolutional neural networks and the per-pixel loss function have shown their potential to be the best combination for super-resolving severely degraded images. However, there are still challenges, such as the massive number of parameters requiring prohibitive memory and vast computing and storage resources [...] Read more.
Convolutional neural networks and the per-pixel loss function have shown their potential to be the best combination for super-resolving severely degraded images. However, there are still challenges, such as the massive number of parameters requiring prohibitive memory and vast computing and storage resources as well as time-consuming training and testing. What is more, the per-pixel loss measured by L2 and the Peak Signal-to-Noise Ratio do not correlate well with human perception of image quality, since L2 simply does not capture the intricate characteristics of human visual systems. To address these issues, we propose an effective two-stage hourglass network with multi-task co-optimization, which enables the entire network to focus on training and testing time and inherent image patterns such as local luminance, contrast, structure and data distribution. Moreover, to avoid overwhelming memory overheads, our model is capable of performing real-time single image multi-scale super-resolution, so it is memory-friendly, meaning that memory space is utilized efficiently. In addition, in order to best use the underlying structure and perception of image quality and the intermediate estimates during the inference process, we introduce a cross-scale training strategy with 2×, 3× and 4× image super-resolution. This effective multi-task two-stage network with the cross-scale strategy for multi-scale image super-resolution is named EMTCM. Quantitative and qualitative experiment results show that the proposed EMTCM network outperforms state-of-the-art methods in recovering high-quality images. Full article
(This article belongs to the Special Issue New Techniques for Image and Video Coding)
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19 pages, 3986 KiB  
Article
A Trellis Based Temporal Rate Allocation and Virtual Reference Frames for High Efficiency Video Coding
by Xiem HoangVan, Le Dao Thi Hue and Thuong Nguyen Canh
Electronics 2021, 10(12), 1384; https://doi.org/10.3390/electronics10121384 - 09 Jun 2021
Viewed by 2063
Abstract
The High Efficiency Video Coding (HEVC) standard has now become the most popular video coding solution for video conferencing, broadcasting, and streaming. However, its compression performance is still a critical issue for adopting a large number of emerging video applications with higher spatial [...] Read more.
The High Efficiency Video Coding (HEVC) standard has now become the most popular video coding solution for video conferencing, broadcasting, and streaming. However, its compression performance is still a critical issue for adopting a large number of emerging video applications with higher spatial and temporal resolutions. To advance the current HEVC performance, we propose an efficient temporal rate allocation solution. The proposed method adaptively allocates the compression bitrate for each coded picture in a group of pictures by using a trellis-based dynamic programming approach. To achieve this task, we trained the trellis-based quantization parameter for each frame in a group of pictures considering the temporal layer position. We further improved coding efficiency by incorporating our proposed framework with other inter prediction methods such as a virtual reference frame. Experiments showed around 2% and 5% bitrate savings with our trellis-based rate allocation method with and without a virtual reference frame compared to the conventional HEVC standard, respectively. Full article
(This article belongs to the Special Issue New Techniques for Image and Video Coding)
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16 pages, 5975 KiB  
Article
VLSI Implementation of a Cost-Efficient Loeffler DCT Algorithm with Recursive CORDIC for DCT-Based Encoder
by Rih-Lung Chung, Chen-Wei Chen, Chiung-An Chen, Patricia Angela R. Abu and Shih-Lun Chen
Electronics 2021, 10(7), 862; https://doi.org/10.3390/electronics10070862 - 05 Apr 2021
Cited by 3 | Viewed by 2313
Abstract
This paper presents a low-cost and high-quality, hardware-oriented, two-dimensional discrete cosine transform (2-D DCT) signal analyzer for image and video encoders. In order to reduce memory requirement and improve image quality, a novel Loeffler DCT based on a coordinate rotation digital computer (CORDIC) [...] Read more.
This paper presents a low-cost and high-quality, hardware-oriented, two-dimensional discrete cosine transform (2-D DCT) signal analyzer for image and video encoders. In order to reduce memory requirement and improve image quality, a novel Loeffler DCT based on a coordinate rotation digital computer (CORDIC) technique is proposed. In addition, the proposed algorithm is realized by a recursive CORDIC architecture instead of an unfolded CORDIC architecture with approximated scale factors. In the proposed design, a fully pipelined architecture is developed to efficiently increase operating frequency and throughput, and scale factors are implemented by using four hardware-sharing machines for complexity reduction. Thus, the computational complexity can be decreased significantly with only 0.01 dB loss deviated from the optimal image quality of the Loeffler DCT. Experimental results show that the proposed 2-D DCT spectral analyzer not only achieved a superior average peak signal–noise ratio (PSNR) compared to the previous CORDIC-DCT algorithms but also designed cost-efficient architecture for very large scale integration (VLSI) implementation. The proposed design was realized using a UMC 0.18-μm CMOS process with a synthesized gate count of 8.04 k and core area of 75,100 μm2. Its operating frequency was 100 MHz and power consumption was 4.17 mW. Moreover, this work had at least a 64.1% gate count reduction and saved at least 22.5% in power consumption compared to previous designs. Full article
(This article belongs to the Special Issue New Techniques for Image and Video Coding)
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17 pages, 985 KiB  
Article
A General Model for the Design of Efficient Sign-Coding Tools for Wavelet-Based Encoders
by Otoniel Mario López-Granado, Miguel Onofre Martínez-Rach, Antonio Martí-Campoy, Marco Antonio Cruz-Chávez and Manuel Pérez Malumbres
Electronics 2020, 9(11), 1899; https://doi.org/10.3390/electronics9111899 - 12 Nov 2020
Viewed by 1499
Abstract
Traditionally, it has been assumed that the compression of the sign of wavelet coefficients is not worth the effort because they form a zero-mean process. However, several image encoders such as JPEG 2000 include sign-coding capabilities. In this paper, we analyze the convenience [...] Read more.
Traditionally, it has been assumed that the compression of the sign of wavelet coefficients is not worth the effort because they form a zero-mean process. However, several image encoders such as JPEG 2000 include sign-coding capabilities. In this paper, we analyze the convenience of including sign-coding techniques into wavelet-based image encoders and propose a methodology that allows the design of sign-prediction tools for whatever kind of wavelet-based encoder. The proposed methodology is based on the use of metaheuristic algorithms to find the best sign prediction with the most appropriate context distribution that maximizes the resulting sign-compression rate of a particular wavelet encoder. Following our proposal, we have designed and implemented a sign-coding module for the LTW wavelet encoder, to evaluate the benefits of the sign-coding tool provided by our proposed methodology. The experimental results show that sign compression can save up to 18.91% of bit-rate when enabling sign-coding capabilities. Also, we have observed two general behaviors when coding the sign of wavelet coefficients: (a) the best results are provided from moderate to high compression rates; and (b) the sign redundancy may be better exploited when working with high-textured images. Full article
(This article belongs to the Special Issue New Techniques for Image and Video Coding)
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