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Energy-Efficient Saliency-Guided video coding Framework for Real-Time Applications

IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS 2025年第1期15卷 44-57页

作者： Partanen, Tero Hoang, Minh Mercat, Alexandre Sainio, Joose Vanne, Jarno Tampere Univ Ultra Video Grp Tampere 33014 Finland

The significant growth in global video data traffic can be mitigated by saliency-based video coding schemes that seek to increase coding efficiency without any loss of objective visual quality by compressing salient video regions less heavily than non-salient regions. However, conducting salient object detection (SOD) on every video frame before encoding tends to lead to substantial complexity and energy consumption overhead, especially if state-of-the-art deep learning techniques are used in saliency detection. This work introduces a saliency-guided video encoding framework that reduces the energy consumption over frame-by-frame SOD by increasing the detection interval and applying the proposed region-of-interest (ROI) tracking between successive detections. The computational complexity of our ROI tracking technique is kept low by predicting object movements from motion vectors, which are inherently calculated during encoding. Our experimental results demonstrate that the proposed ROI tracking solution saves energy by 86-95% and attains 84-94% accuracy over frame-by-frame SOD. Correspondingly, integrating our proposal into the complete saliency-guided video coding scheme reduces energy consumption on CPU by 79-82% at a cost of weighted PSNR of less than 5%. These findings indicate that our solution has significant potential for low-cost and low-power streaming media applications.

关键词： Encoding Streaming media video coding Image coding Saliency detection Energy efficiency Energy consumption Visualization Object tracking Computational modeling Saliency-guided encoding region-of-interest (ROI) ROI tracking deep learning (DL) motion vector (MV)

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Screen Content-Aware video coding Through Non-Local Model Embedded With Intra-Inter In-Loop Filtering

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR video TECHNOLOGY 2025年第2期35卷 1870-1883页

作者： Li, Mingxuan Ji, Wen Chinese Acad Sci Inst Comp Technol Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Comp Sci & Technol Beijing 100190 Peoples R China LonganPi Intelligent Informat Technol Co Ltd Beijing 100080 Peoples R China

Many studies have focused on utilizing convolutional neural networks (CNNs) to enhance loop filter performance in video encoding. However, existing methods primarily concentrate on improving the natural sequence quality rather than addressing the specific needs of screen content sequences, which have gained increased attention due to the growing demands of remote desktops and online meetings. This paper proposed to understand machine behavior from the machine's point of view, and adopts the machine intelligence to screen content coding. It presents a novel loop filter specifically tailored for screen content coding (SCC), referred to as video coding-SCC (VC-SCC). It employs a multiscale feature extraction structure and introduces two innovative non-local models to address distortions in different frame types across various coding setups. Specifically, considering regions of text and graphic textures in screen content, three types of prior maps, including screen content maps, coding configuration maps, and traditional filtering maps, are designed as auxiliary information in the model, promoting distortion pattern learning under different configurations. Two novel non-local models are proposed to enhance the model's ability to capture global features in intra- and inter-frames while keeping low computational complexity. Finally, the VC-SCC is proposed for parallel implementation with the standard in-loop filter, and the optimal results are selected in each patch. Experimental results demonstrate significant performance improvements, with average BD-rate savings of 9.93%, 11.05%, and 10.73% for the all-intra(AI), low-delay(LD), and random-access(RA) configurations, respectively, outperforming other state-of-the-art approaches.

关键词： Encoding Feature extraction Computational modeling Adaptation models Visualization Nonlinear distortion Information filters Deep learning Standards Image color analysis video coding in-loop filtering screen content deep learning high-efficiency video coding (HEVC)

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Convolutional Cross-Component Models for Chroma Prediction in video coding

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR video TECHNOLOGY 2025年第3期35卷 2854-2869页

作者： Astola, Pekka Aminlou, Alireza Youvalari, Ramin G. Lainema, Jani Nokia Technol Tampere 33100 Finland Xiaomi Technol Tampere 33100 Finland

In this paper we present two novel approaches for improving intra and inter chroma prediction in video coding. Our research demonstrates that treating the cross-component predictor as a two-dimensional convolutional model can significantly enhance chroma prediction performance. The proposed two convolutional models incorporate multiple spatial neighbors, a bias term, and a nonlinear term. For intra-coded blocks, we derive the model coefficients on the reconstructed neighborhood of the block, while for inter-coded blocks, the model coefficients are determined using prediction samples. To evaluate our methods, we implemented them on top of the ECM software that is currently under exploration by the ITU-T/ISO/IEC Joint video Experts Team. Our intra cross-component predictor achieves BD-rate savings of {-1.47%, -2.90%, -3.02%}, {-0.92%, -2.04%, -2.32%} (Y, U, V) for the all intra and the random access configurations over ECM-5.0, respectively. Our inter cross-component predictor achieves BD-rate savings of {-0.09%, -1.25%, -1.46%}, {-0.04%, -3.42%, -3.85%} for the random access and the low-delay B configurations over ECM-9.0, respectively. Both proposed methods have been adopted into the ECM software.

关键词： Predictive models Convolutional codes Encoding video coding Streaming media Image coding Transforms Software Image reconstruction Filters versatile video coding chroma prediction

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A Survey on Recent Advances in video coding Technologies and Future Research Directions

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IEEE TRANSACTIONS ON BROADCASTING 2025年

作者： Guo, Houbang Zhou, Yun Guo, Hongwei Jiang, Zhuqing He, Tian Wu, Yiyan UCL Phys & Astron Dept London WC1E 6BT England NRTA Acad Broadcasting Sci TV Technol Inst Beijing 100866 Peoples R China Honghe Univ Sch Engn Mengzi 661100 Peoples R China Beijing Univ Posts & Telecommun Sch Artificial Intelligence Beijing 100876 Peoples R China Western Univ Dept Elect & Comp Engn London ON N6A 5B9 Canada

With the evolution of video coding, balancing video compression efficiency with quality has become a critical challenge for researchers and the industry. The development of the next-generation video coding standards, such as Versatile video coding (VVC), signifies a significant leap in supporting high-resolution formats including 8K, HDR, and WCG. Currently, machine vision has emerged as a rising research focus, driven by breakthrough in Artificial Intelligence and its growing role in content generation, production, distribution, and storage in multimedia applications. This paper presents a comprehensive survey of the video coding tools in the VVC standard. Additionally, we examine recent research in next-generation video coding, particularly in Beyond VVC and end-to-end coding frameworks. Developments in shared human-machine vision systems are also discussed, emphasizing their relevance in evolving multimedia applications. Finally, this paper provides an outlook on video coding standards, considering their potential to drive next-generation multimedia technologies.

关键词： video coding Encoding Machine vision Standards Color Streaming media Transforms video recording video compression Quantization (signal) video coding standards versatile video coding (VVC) beyond VVC machine vision

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Empowering Computer Vision in Higher Education: A Novel Tool for Enhancing video coding Comprehension

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COMPUTER APPLICATIONS IN ENGINEERING EDUCATION 2025年第1期33卷

作者： Cuevas, Carlos Cortes, Carlos Garcia, Narciso Univ Politecn Madrid UPM Informat Proc & Telecommun Ctr IPTC Grp Tratamiento Imagenes GTI Madrid Spain Univ Politecn Madrid UPM ETSI Telecomunicac Madrid Spain

The growing demand for skilled computer vision professionals requires effective educational approaches. This study explores a novel tool based on Virtual Programming Language principles designed to enhance computer vision education, specifically in video coding. The tool leverages a user-friendly interface and a custom widget library for video exploration, enabling students to engage with video data manipulation, motion estimation simulations, and visualization of coding effects. A controlled experiment with computer vision students from a university master's program demonstrates that the tool significantly improves student motivation, knowledge acquisition, and overall learning outcomes. This study highlights the potential of such tools to revolutionize computer vision education, leading to better engagement, deeper understanding, and enhanced practical skills. Therefore, it paves the way for further exploration of similar tools in computer vision and other science, technology, engineering, and mathematics disciplines.

关键词： computer vision education knowledge acquisition student motivation video coding virtual programming languages

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Fast Integer Simplified Sine-Cosine Transform Type VII of Order 16 for video coding

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CYBERNETICS AND SYSTEMS ANALYSIS 2025年第2期61卷 319-331页

作者： Luts, Ya. V. Natl Acad Sci Ukraine VM Glushkov Inst Cybernet Kyiv Ukraine

The matrix method for constructing integer simplified sine-cosine transforms type VII of order 16 is developed based on two transforms of order 8: sine type VII and cosine type II. Two integer single-norm simplified sine-cosine transforms of low computational complexity are developed, which is 38.6% less compared to the well-known discrete sine transform type VII of order 16 algorithm with integer approximation. The resulting transforms have a 1 to 1.5% lower compression ratio with the same quality of restored data;therefore, they can be used for the scheme of separable adaptive transforms for high-speed image and video coding modes.

关键词： discrete cosine transform discrete sine transform integer cosine transform integer sine transform integer sine-cosine transform scaled transform separable adaptive transforms factorization video coding H.265 VVC (Versatile video coding) MTS (Multiple Transform Selection)

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Fast Integer Sine and Cosine Transforms Type IV of Low Complexity for video coding

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CYBERNETICS AND SYSTEMS ANALYSIS 2025年第2期61卷 305-318页

作者： Hnativ, L. O. Natl Acad Sci Ukraine VM Glushkov Inst Cybernet Kyiv Ukraine

The matrix methods for constructing integer sine and cosine transforms type IV (IST-IV / ICT-IV) of orders 8 and 16 are proposed, based on which two integer transforms of type IV are constructed and fast algorithms for their calculation that only require operations with integers are developed. The algorithms for calculating IST-IV/ ICT-IV of order 16 require, respectively, 14.29% and 12.5% fewer multiplication operations and 22.11% and 20.83% more addition operations compared to the known algorithms for discrete sine and cosine transforms type IV. The proposed fast IST-IV/ ICT-IV compared to the known fast discrete sine type VII and cosine type VIII transforms with integer approximation from the VVC standard (DST-VII/DCT-VIII) have 3.02 times less multiplicative complexity and require 47.41% fewer addition operations. Fast algorithms of low computational complexity for computing 2D separable integer cosine type II and sine type IV adaptive transforms for intra-prediction with image blocks have been developed, which have 2.66 times less multiplicative complexity and require 28.9% fewer addition operations compared to the known separable transforms ICT-II (H.265)/DST-VII (VVC).

关键词： discrete cosine transform discrete sine transform integer cosine transform integer sine transform factorization video coding H.265 VVC (Versatile video coding) separable adaptive transform MTS (Multiple Transform Selection)

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Chained Motion Vector Prediction for video coding

Chained Motion Vector Prediction for Video Coding

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yoshitaka Kidani Haruhisa Kato Kei Kawamura KDDI Research Inc. Saitama Japan

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Merge mode has been utilized in advanced video coding standards to facilitate the efficiency of Motion vector (MV) or Block Vector (BV) coding. Merge mode constructs multiple MVs or BVs as the merge candidate list from MV/BV storage and then specifies one within the list by signaling the merge index. Despite various merge candidate derivation methods in prior arts, they do not adequately reach MV/BV, pointing to reference pictures with low quantization noise, leaving room for improved coding performance. This paper proposes a Chained Motion Vector Prediction (CMVP) as a novel merge candidate derivation. The CMVP derives new candidates by accumulating the recursively traced MVs or BVs based on pre-derived merge candidates. Experimental results demonstrate that the proposed method achieves up to 1.01% coding gains with negligible complexity increases on version 12 of Enhanced Compression Model (ECM), a reference software for evaluating promising coding tools beyond Versatile video coding (VVC).

关键词： video coding Runtime Quantization (signal) Speech coding Noise Vectors Encoding Software Speech processing Standards

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Analysis of the Intra-Picture coding Tools of Versatile video coding (VVC) Standard for 8K video Resolution

Analysis of the Intra-Picture Coding Tools of Versatile Vide...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Altuğ Şimşek Günhan Dündar Electrical & Electronics Engineering Dept. Boğaziçi University Istanbul Türkiye

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

Versatile video coding (VVC), standardized in 2022 as ITU-T Recommendation H.266, ISO/IEC 23090–3 and MPEG-I Part3, is the latest block-based hybrid video coding standard which claims to fulfill all the requirements of todays and tomorrow's video applications. VVC defines more tools to increase compression efficiency while maintaining the same level of quality. The tradeoff is the computational complexity. H.266/VVC, especially the intra-coding loop, is computationally very complex due to its nature of iteratively trying all possible QTMT partitioning tree alternatives with all options of compression technologies. In this paper, we focus on the intra-coding loop of VVC for 8K video and study the effects of technologies like MTS, LFNST, MIP etc. on the compression efficiency (bits), quality (Y-PSNR), and computational complexity (runtime). By switching off all those optional technologies, we observe 46.07% runtime gain with only 5.00% increase in bitrate, and 0.0423 dB decrease in Y-PSNR on average. Since this is a remarkable gain in complexity with a limited effect on efficiency and quality, this tradeoff can be taken into consideration for many 8K applications utilizing VVC.

关键词： video coding Runtime ISO Standards Bit rate Transform coding Switches Partitioning algorithms Computational complexity Standards Gain

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Exploration of Sequence-wise Optimized Parameters for Low Complexity Enhancement video coding (LCEVC) on 4K Content

Exploration of Sequence-wise Optimized Parameters for Low Co...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Martin Benjak Jörn Ostermann Institute for Information Processing Leibniz Universität Hannover Hanover Germany

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

This paper explores the configuration space of Low Complexity Enhancement video coding (LCEVC) for 4K SDR content and the VVC reference software VTM as base layer codec. The configuration space is spanned using a sweep over multiple values for the base layer QP and the LCEVC parameters sublayer 2 step width, scaling mode, number of processed picture planes, transformation type, and sequence-wise optimized upscaling filter coefficients. The best configurations are selected using a convex hull approach. Compared to the default LCEVC configuration, we achieve average BD-rate gains of 10.92% and 2.06% using 1d and 2d upscaling, respectively. However, our best possible LCEVC configuration still yields an average YCbCr BD-rate loss of 15.26% compared to VTM at full resolution.

关键词： video coding Convex hulls Codecs Speech coding Software Acoustics Space exploration Complexity theory Speech processing Signal resolution

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