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

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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...

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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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Dynamic Template Update Mechanism for visual Object Tracking

Dynamic Template Update Mechanism for Visual Object Tracking

引用

6th International conference on Intelligent Computing and Signal processing (ICSP)

作者： YongQi Hu ZhongWang Cai ZiJun Nie ZiZheng Yu Ying Cao Zhijian Yin Zhen Yang School of Communications and Electronics Jiangxi Science and Technology Normal University Nanchang China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai China

Given the requirements for robust target classification and accurate target state estimation in visual tracking, SiamFC++ proposes a set of practical guidelines for designing high-performance general-purpose trackers by considering the special nature of visual tracking problems. Inspired by dynamic modules, We propose an empirical method for integrating a dynamic module into the image input, which is concatenated with the template module after feature maps are extracted by the backbone network. Since the position and shape of the object can change significantly within a video sequence, the added dynamic module can better focus on the target region of the feature map to obtain better similarity maps. Extensive experiments and comparisons demonstrate that our simple and effective method achieves reliable results on the benchmarks of LaSOT, TrackingNet, and GOT-10K and provides a significant speed advantage in real-time.

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Two-Stage Robust Reversible image Watermarking Based on Deep Neural Network 8th

Two-Stage Robust Reversible Image Watermarking Based on Deep...

引用

8th International conference on Artificial Intelligence and Security , ICAIS 2022

作者： Huang, Jie Li, Fengyong Zhang, Lei Qin, Chuan School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China College of Computer Science and Technology Shanghai University of Electric Power Shanghai200090 China Guangxi Key Lab of Multi-Source Information Mining and Security Guangxi Normal University Guilin541004 China Computer Science Department University of Victoria VictoriaBC Canada

ISBN: (纸本)9783031067631

This paper proposes a two-stage lossless robust watermarking scheme based on deep neural network. In the first stage, the encoder, noise layer and decoder network are combined to design an end-to-end network framework, which is used to train the input watermark information and cover image. In this framework, the encoder outputs a robust watermarked image whose visual quality is similar to the cover image, and the decoder can extract the embedded watermark information to evaluate robustness. In the second stage, by using reversible information hiding algorithm with extended prediction error, the auxiliary information that can recover the cover image is embedded into the robust watermarked image to ensure reversibility. If the watermarked image does not undergo attack processing, the hidden watermark information can not only be extracted, but also the cover image can be completely recovered. Even if the watermarked image does undergo attack processing, the embedded watermark information can also be extracted correctly because of the strong robustness in the first stage. Experimental results demonstrate the robustness of proposed scheme in terms of JPEG compression, gaussian filtering noise, rotation and shearing operations. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Deep neural networks

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