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Fast CU Partition Method Based on Extra Trees for VVC Intra Coding

Fast CU Partition Method Based on Extra Trees for VVC Intra ...

引用

IEEE visual communications and image processing (VCIP)

作者： Kaijie Wang Hong Liang Saiping Zhang Fuzheng Yang School of Telecommunications Engineering Xidian University Xi'an China

ISBN: (纸本)9781665475938

In this paper, we propose a method to skip unnecessary CU encoding modes for VVC Intra coding based on the extra trees model. Two extra tree models with calculated features are used to simplify the encoding process, where the first model determines whether to early terminate the partition and the best partition direction and the second model selects the better partition mode between the binary and ternary partition modes. Experimental results show that our proposed method can save encoding time from 34.68% to 46.70 % with only from 0.81% to 1.65% increase of BDBR compared to VVC reference software (VTM 10.0). Besides, the method gets a great tradeoff when applied on VVenC 1.0, an efficient encoder ofVVC, at both preset slower and preset medium.

关键词： image coding visual communication Software Distance measurement

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Autoencoder-based intra prediction with auxiliary feature

Autoencoder-based intra prediction with auxiliary feature

引用

IEEE visual communications and image processing (VCIP)

作者： Luhang Xu Yue Yu Haoping Yu Dong Wang Department of Standards Research OPPO Nanjing JiangSu China

ISBN: (纸本)9781665475938

A set of auto encoders is trained to perform intra prediction for block-based video coding. Each auto encoder consists of an encoding network and a decoding network. Both encoding network and decoding networks are jointly optimized and integrated into the state-of-the-art VVC reference software VTM-11.0 as an additional intra prediction mode. The simulation is conducted under common test conditions with all intra config-urations and the test results show 1.55%, 1.04%, and 0.99% of Y, U, V components Bjentegaard-Delta bit rate saving compared to VTM-11.0 anchor, respectively. The overall relative decoding running time of proposed autoencoder-based intra prediction mode on top of VTM-11.0 are 408% compared to VTM-11.0.

关键词： Video coding Training image coding visual communication Bit rate Software Decoding

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Multi-focus Fusion Using image Matting and Geometric Mean of DCT-Variance 1

引用

5th International conference on Computer Vision and image processing, CVIP 2020

作者： Roy, Manali Mukhopadhyay, Susanta Dhanbad India

ISBN: (数字)9789811610868

ISBN: (纸本)9789811610851

Optical lenses installed in most imaging devices suffer from the limited depth of field due to which objects get imaged with varying sharpness and details, thereby losing essential information. To cope with the problem, an effective multi-focus fusion technique is proposed in this paper based on a focus measure obtained from the statistical properties of an image and its DCT-bandpass filtered versions. The focus information obtained is eventually converted into a decision trimap using fundamental image processing operations. This trimap largely discriminates between the focussed and defocussed pixels and expedites the fusion process by acting as an input to a robust image matting framework to obtain a final decision map. Experimental results illustrate the superiority of the proposed approach over other competing multi-focus methods in terms of visual quality and fusion metrics. © 2021, Springer Nature Singapore Pte Ltd.

关键词： image fusion

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Self-Supervised Dense visual Representation Learning

Self-Supervised Dense Visual Representation Learning

引用

IEEE Signal processing and communications Applications (SIU)

作者： Timoteos Onur Özçelİk Berk Gökberk Lale Akarun Bilgisayar Mühendisliği Boğaziçi Üniversitesi ˙Istanbul Türkiye

ISBN: (数字)9798350388961

ISBN: (纸本)9798350388978

Self-supervised representation learning has shown promising results in recent years. However, most of the proposed methods are pre-trained on object-centric datasets with image-level pretext tasks. In this study, we follow DenseCL, which is pre-trained on pixel-level scene-centric datasets with contrastive learning. Our goal is to alleviate the false negative pairing problem in contrastive learning by consistency regularization. Our method outperforms DenseCL and PixContrast models in most of the scenarios. In PASCAL VOC object detection, we see 0.2% AP50 and 0.3% AP improvements. In COCO object detection, we get 0.3% AP and 0.7% AP boosts. We also improve by 0.4% AP and 0.6% AP in COCO instance segmentation, and 0.1% mAP and 0.9% mAP in PASCAL VOC semantic segmentation. Moreover, attention map visualization and k-nearest neighbour retrieval indicate qualitative improvement from the proposed method.

关键词： Representation learning Instance segmentation visualization Semantic segmentation Object detection Contrastive learning Signal processing

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Improving Latent Quantization of Learned image Compression with Gradient Scaling

Improving Latent Quantization of Learned Image Compression w...

引用

IEEE visual communications and image processing (VCIP)

作者： Heming Sun Lu Yu Jiro Katto Waseda Research Institute for Science and Engineering Waseda University Tokyo Japan Institutc of Information and Communication Engineering Zhejiang University Hangzhou China JST PRESTO Kawaguchi Saitama Japan Department of Computer Science and Communication Engineering Waseda University Tokyo Japan

ISBN: (纸本)9781665475938

Learned image compression (LIC) has shown its superior compression ability. Quantization is an inevitable stage to generate quantized latent for the entropy coding. To solve the non-differentiable problem of quantization in the training phase, many differentiable approximated quantization methods have been proposed. However, the derivative of quantized latent to non-quantized latent are set as one in most of the previous methods. As a result, the quantization error between non-quantized and quantized latent is not taken into consideration in the gradient descent. To address this issue, we exploit the gradient scaling method to scale the gradient of non-quantized latent in the back-propagation. The experimental results show that we can outperform the recent LIC quantization methods.

关键词： Training Quantization (signal) image coding visual communication Entropy coding Tuning

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Asynchronous Autoregressive Prediction for Satellite Anomaly Detection

Asynchronous Autoregressive Prediction for Satellite Anomaly...

引用

IEEE visual communications and image processing (VCIP)

作者： Peng Liu Haopeng Zhang Lifang Yuan Borui Zhang Chengkun Wang Beijing Institute of Spacecraft System Engineering China Department of Automation Tsinghua University China

ISBN: (纸本)9781665475938

This paper proposes an ASynchronous Autoregressive Prediction (ASAP) method for satellite anomaly detection. We empirically observe that a single classification model can hardly detect unknown anomalous situations and neglect the Markov nature of temporal satellite data. To address this, we adopt an autoregressive model to deal with the prediction of unknown anomaly for satellite data. We further propose a non-uniform temporal encoding method for asynchronous data and a median filtering method for more accurate detection. To reduce the effect of outliers, we employ an adaptive threshold selection method to achieve a more robust classification boundary. Experiments on real satellite data demonstrate that the proposed ASAP method outperforms the baseline classification method by 55.79%.

关键词： Adaptation models Satellites image coding Filtering visual communication Predictive models Markov processes

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Performance Analysis of WebRTC Embedding Optimized HEVC CodeC

Performance Analysis of WebRTC Embedding Optimized HEVC Code...

引用

IEEE visual communications and image processing (VCIP)

作者： Zhenyu Liu Yuanfudao Inc

ISBN: (纸本)9781665475938

Web Real-Time communications (WebRTC) is an open-source platform, supporting developer to build voice- and video-communication solutions. Video compression engine is one infrastructure in WebRTC. As video stream accounting for more than 90% bandwidth requirement in real-time communication. The performance of embedded video encoder in WebRTC determines the Quality of Experience of communication, including the picture quality, the communication latency and the playback smoothness. In our WebRTC, we implemented the high performance HEVC software encoder as a substitute of the VP8 encoder in WebRTC. We improve the compression efficiency of HEVC encoder significantly. As compared with the most advanced x265, the averaged 34.6% rate saving was achieved by our encoder, especially in low-latency coding applications. As compared to the default WebRTC integrated with VP8, up to 90.2% bandwidth requirement was saved by our optimizations.

关键词： image coding visual communication Bit rate Bandwidth Streaming media Video compression Software

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Structure-Texture Decomposition-Based Enhancement Framework for Weakly Illuminated images 6th

Structure-Texture Decomposition-Based Enhancement Framework ...

引用

6th International conference on Computer Vision and image processing, CVIP 2021

作者： Haritha, K.M. Sreeni, K.G. Zacharias, Joseph Jeena, R.S. Department of Electronics and Communication Engineering College of Engineering Trivandrum Thiruvananthapuram India

ISBN: (纸本)9783031113451

images acquired in poor illumination conditions are characterized by low brightness and considerable noise which constrain the performance of computer vision systems. image enhancement thus remains crucial for improving the efficiency of such systems. To improve the visibility of low-light images, a novel image enhancement framework based on the structure-texture decomposition is proposed in this paper. Firstly, the low-light image is split into structure and texture layers using the total-variation (TV) based image decomposition approach. The structure layer is initially diffused using Perona-Malik (PM) diffusion model and the local and global luminance enhancement is incorporated in the structure-pathway using an expanded model of biological normalization for visual adaptation. In the texture pathway, the suppression of local noise and the enhancement of image details are attained with the estimation of the local energy of the texture layer and the strategy of energy weighting. Eventually, the final enhanced image of improved quality is obtained by merging the modified structure and texture layers. The effectiveness of the proposed framework is validated using no-reference image quality metrics including IL-NIQE, BRISQUE, PIQE, and BLIINDS-II. The experimental results show that the proposed method outperforms the state-of-the-art approaches. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： image enhancement

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MSCI: A Multi-Source Composite image Database for Compression Distortion Quality Assessment

MSCI: A Multi-Source Composite Image Database for Compressio...

引用

IEEE visual communications and image processing (VCIP)

作者： Xiaofang Zhang Zhuowei Xu Zhiheng Lin Miaohui Wang College of Information and Electronics Engineering Shenzhen University P. R. China College of Marine Equipment and Mechanical Engineering Jimei University Xiamen P. R. China

ISBN: (纸本)9781665475938

With the rapid development of multi-sensor fusion technology in various industrial fields, many composite images closely related to human life have been produced. To meet the rapidly growing needs of various image-based applications, we have established the first multi-source composite image (MSCI) database for image quality assessment (IQA). Our MSCI database contains 80 reference images and 1600 distorted images, generated by four advanced compression standards with five distortion levels. In particular, these five distortion levels are determined based on the first five just noticeable difference (JND) levels. Moreover, we verify the IQA performance of some representative methods on our MSCI database. The experimental results show that the performance of the existing methods on the MSCI database needs to be further improved.

关键词： image quality image coding visual communication image databases Distortion Quality assessment Standards

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A Systematic Literature Review on image Captioning 25th

A Systematic Literature Review on Image Captioning

引用

25th International conference on Human-Computer Interaction, HCII 2023

作者： Ding, Yi Tongji University Shanghai200092 China

ISBN: (纸本)9783031360039

image captioning is a technology that generates textual descriptions of images by integrating computer vision and natural language processing. This review aims to provide a comprehensive overview of current state-of-the-art image captioning models and techniques, summarize the critical approaches, evaluate their performance on benchmark datasets, highlight main challenges and limitations, and provide insights into future research directions. The systematic literature review followed a PRISMA-based approach and formulated three research questions (RQs) to construct the review. The study extracted and synthesized data from 49 eligible papers on visual and language models, datasets employed, and evaluation mechanisms used to measure performance. We found that it is evident that large-scale models and pre-training strategies have significantly advanced the field of image captioning. Specific sub-tasks for image captioning in certain applications have also contributed to the development of unique datasets. Future research directions in image captioning can be focused on solving the issues of expensive and scarce paired datasets, as well as shifting towards user-centric sub-tasks from generalization. This review can serve as a valuable resource for researchers, practitioners, and enthusiasts interested in image captioning. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Benchmarking

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