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iWave3D: End-to-end Brain image Compression with Trainable 3-D Wavelet Transform

iWave3D: End-to-end Brain Image Compression with Trainable 3...

引用

IEEE visual communications and image processing (VCIP)

作者： Dongmei Xue Haichuan Ma Li Li Dong Liu Zhiwei Xiong University of Science and Technology of China Hefei China

ISBN: (纸本)9781728173221

With the rapid development of whole brain imaging technology, a large number of brain images have been produced, which puts forward a great demand for efficient brain image compression methods. At present, the most commonly used compression methods are all based on 3-D wavelet transform, such as JP3D. However, traditional 3-D wavelet transforms are designed manually with certain assumptions on the signal, but brain images are not as ideal as assumed. What's more, they are not directly optimized for compression task. In order to solve these problems, we propose a trainable 3-D wavelet transform based on the lifting scheme, in which the predict and update steps are replaced by 3-D convolutional neural networks. Then the proposed transform is embedded into an end-to-end compression scheme called iWave3D, which is trained with a large amount of brain images to directly minimize the rate-distortion loss. Experimental results demonstrate that our method outperforms JP3D significantly by 2.012 dB in terms of average BD-PSNR.

关键词： Wavelet transforms Neuroimaging Brain image coding visual communication Rate-distortion Entropy

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Real-time embedded hologram calculation for augmented reality glasses

Real-time embedded hologram calculation for augmented realit...

引用

IEEE visual communications and image processing (VCIP)

作者： Antonin Gilles Advanced Media Content Laboratory Research & Technology Institute b<>com Rennes France

ISBN: (纸本)9781728173221

Thanks to its ability to provide accurate focus cues, Holography is considered as a promising display technology for augmented reality glasses. However, since it contains a large amount of data, the calculation of a hologram is a time-consuming process which results in prohibiting head-motion-to-photon latency, especially when using embedded calculation hardware. In this paper, we present a real-time hologram calculation method implemented on a NVIDIA Jetson AGX Xavier embedded platform. Our method is based on two modules: an offline pre-computation module and an on-the-fly hologram synthesis module. In the offline calculation module, the omnidirectional light field scattered by each scene object is individually pre-computed and stored in a Look-Up Table (LUT). Then, in the hologram synthesis module, the light waves corresponding to the viewer's position and orientation are extracted from the LUT in real-time to compute the hologram. Experimental results show that the proposed method is able to compute 2K1K color holograms at more than 50 frames per second, enabling its use in augmented reality applications.

关键词： image color analysis visual communication Redundancy Glass Real-time systems Hardware Light fields

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Rethinking Anchor-Object Matching and Encoding in Rotating Object Detection

Rethinking Anchor-Object Matching and Encoding in Rotating O...

引用

IEEE visual communications and image processing (VCIP)

作者： Zhiyuan Huang Zhaohui Hou Pingyu Wang Fei Su Zhicheng Zhao School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing China Beijing Key Laboratory of Network System and Network Culture Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781728173221

Rotating object detection is more challenging than horizontal object detection because of the multi-orientation of the objects involved. In the recent anchor-based rotating object detector, the IoU-based matching mechanism has some mismatching and wrong-matching problems. Moreover, the encoding mechanism does not correctly reflect the location relationships between anchors and objects. In this paper, RBox-Diff-based matching (RDM) mechanism and angle-first encoding (AE) method are proposed to solve these problems. RDM optimizes the anchor-object matching by replacing IoU (Intersection-over-Union) with a new concept called RBox-Diff, while AE optimizes the encoding mechanism to make the encoding results consistent with the relative position between objects and anchors more. The proposed methods can be easily applied to most of the anchor-based rotating object detectors without introducing extra parameters. The extensive experiments on DOTA-v1.0 dataset show the effectiveness of the proposed methods over other advanced methods.

关键词： image coding visual communication Object detection Detectors

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Gradient Compression with a Variational Coding Scheme for Federated Learning

Gradient Compression with a Variational Coding Scheme for Fe...

引用

IEEE visual communications and image processing (VCIP)

作者： Birendra Kathariya Zhu Li Jianle Chen Geert Van Der Auwera University of Missouri-Kansas City Kansas City USA Qualcomm San Diego USA

ISBN: (纸本)9781728173221

Federated Learning (FL), a distributed machine learning architecture, emerged to solve the intelligent data analysis on massive data generated at network edge-devices. With this paradigm, a model is jointly learned in parallel at edge-devices without needing to send voluminous data to a central FL server. This not only allows a model to learn in a feasible duration by reducing network latency but also preserves data privacy. Nonetheless, when thousands of edge-devices are attached to an FL framework, limited network resources inevitably impose intolerable training latency. In this work, we propose model-update compression to solve this issue in a very novel way. The proposed method learns multiple Gaussian distributions that best describe the high dimensional gradient parameters. In the FL server, high dimensional gradients are repopulated from Gaussian distributions utilizing likelihood function parameters which are communicated to the server. Since the distribution information parameters constitute a very small percentage of values compared to the high dimensional gradients themselves, our proposed method is able to save significant uplink band-width while preserving the model accuracy. Experimental results validated our claim.

关键词： Training image coding visual communication Distributed databases Machine learning Gaussian distribution Collaborative work

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A Bottom-up Fast CU Partition Scoring Mechanism for AVS3

A Bottom-up Fast CU Partition Scoring Mechanism for AVS3

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IEEE visual communications and image processing (VCIP)

作者： Shiyi Liu Zhenyu Wang Ke Qiu Jiayu Yang Ronggang Wang School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Shenzhen China

ISBN: (纸本)9781728173221

The third generation of Audio Video Coding Standard (AVS3) achieves 22% coding performance improvement compared with High Efficiency Video Coding (HEVC). However, the improvement of encoding efficiency comes from a more flexible block partition scheme is at the cost of much higher encoding complexity. This paper proposes a bottom-up fast algorithm to prune the time-consuming search process of the CU partition tree. To be specific, we design a scoring mechanism based on the splitting patterns traced back from the bottom to predict the possibility of a partition type to be selected as optimal. The score threshold to skip the exhaustive Rate-Distortion Optimization (RDO) procedure of the partition type is determined by statistical analysis. The experimental results show that the proposed methods can achieve 24.56% time-saving with 0.37% BDBR loss under Random Access configuration and 12.50% complexity reduction with 0.08% BDBR loss under All Intra configuration. The effectiveness leads to the adoption by the open-source platform of AVS3 after evaluated by the AVS working group.

关键词： image coding visual communication Statistical analysis Software algorithms Rate-distortion Encoding Complexity theory

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An Intra String Copy Approach for SCC in AVS3

An Intra String Copy Approach for SCC in AVS3

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IEEE visual communications and image processing (VCIP)

作者： Liping Zhao Kailun Zhou Qingyang Zhou Huihui Wang Tao Lin Shaoxing University Shaoxing China Information Technology R&D Innovation Center of Peking University Shaoxing China VLSI Lab College of Electronics and Information Engineering Tongji University Shanghai China

ISBN: (纸本)9781728173221

An efficient SCC tool named Intra String Copy (ISC) has been proposed and adopted in AVS3 recently. ISC has two CU-level sub-modes: FPSP (fully-matching-string and partially-matching-string based string prediction) sub-mode and EUSP (equal-value-string, unit-basis-vector-string and unmatched-pixel-string based string prediction) sub-mode. Compared with the latest AVS3 reference software HPM with SCC tools disabled, using AVS3 SCC Common Test Condition and YUV test sequences in text and graphics with motion (TGM) and mixed content (MC) categories, the proposed tool achieves an average Y BD-rate reduction of 57.7%/39.5% and 77.2%/57.9% for TGM and MC in All Intra (AI)/Low Delay B(LDB) configurations, respectively, with low additional encoding complexity and almost the same decoding complexity.

关键词： Graphics image coding visual communication Software Complexity theory Delays Decoding

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Deep Color Constancy Using Spatio-Temporal Correlation of High-Speed Video

Deep Color Constancy Using Spatio-Temporal Correlation of Hi...

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IEEE visual communications and image processing (VCIP)

作者： Dong-Jae Lee Kang-Kyu Lee Jong-Ok Kim Korea University Seoul Korea

ISBN: (纸本)9781728173221

After the invention of electric bulbs, most of lights surrounding our worlds are powered by alternative current (AC). This intensity variation can be captured with a high-speed camera, and we can utilize the intensity difference between consecutive video frames for various vision tasks. For color constancy, conventional methods usually focus on exploiting only the spatial feature. To overcome the limitations of conventional methods, a couple of methods to utilize AC flickering have been proposed. The previous work employed temporal correlation between high-speed video frames. To further enhance the previous work, we propose a deep spatio-temporal color constancy method using spatial and temporal correlations. To extract temporal features for illuminant estimation, we calculate the temporal correlation between feature maps where global features as well as local are learned. By learning global features through spatio-temporal correlation, the proposed method can estimate illumination more accurately, and is particularly robust to noisy practical environments. The experimental results demonstrate that the performance of the proposed method is superior to that of existing methods.

关键词： Technological innovation Correlation image color analysis visual communication Lighting Estimation Feature extraction

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Deep Inter Prediction via Reference Frame Interpolation for Blurry Video Coding

Deep Inter Prediction via Reference Frame Interpolation for ...

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IEEE visual communications and image processing (VCIP)

作者： Zezhi Zhu Lili Zhao Xuhu Lin Xuezhou Guo Jianwen Chen School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781728173221

In High Efficiency Video Coding (HEVC), inter prediction is an important module for removing temporal redundancy. The accuracy of inter prediction is much affected by the similarity between the current and reference frames. However, for blurry videos, the performance of inter coding will be degraded by varying motion blur, which is derived from camera shake or the acceleration of objects in the scene. To address this problem, we propose to synthesize additional reference frame via the frame interpolation network. The synthesized reference frame is added into reference picture lists to supply more credible reference candidate, and the searching mechanism for motion candidates is changed accordingly. In addition, to make our interpolation network more robust to various inputs with different compression artifacts, we establish a new blurry video database to train our network. With the well-trained frame interpolation network, compared with the reference software HM-16.9, the proposed method achieves on average 1.55% BD-rate reduction under random access (RA) configuration for blurry videos, and also obtains on average 0.75% BD-rate reduction for common test sequences.

关键词： Interpolation image coding visual communication Databases Redundancy Cameras Software

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Alignment-Free Video Compression Artifact Reduction

Alignment-Free Video Compression Artifact Reduction

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IEEE visual communications and image processing (VCIP)

作者： Dengyan Luo Mao Ye Shengjie Chen Xue Li University of Electronic Science and Technology of China The University of Queensland

ISBN: (纸本)9781728173221

The past few years have witnessed the great success of using multi-frame information to enhance the quality of compressed video. Most existing methods do frame or feature alignments to bring similar information from neighborhood frames much closer to enhance frame quality. However, inaccurate motion estimation will bring new artifacts. In this paper, we propose a new approach without alignment, which takes each non-Peak Quality Frame (non-PQF) and its two adjacent Peak Quality Frames (PQFs) as input. A Pre-processing module based on multi-scale feature extraction strategy is used to broaden receptive field of the network. Then, an enhancement module uses a two-stream feature extraction architecture to combine deep architecture and attention mechanism to further gather similar information. In this module, the lost high-frequency and similar information can be further retrieved from the adjacent PQFs. The proposed network is trained in an end-to-end manner. Compared with the alignment based methods, the competitive results can be obtained. A large number of qualitative and quantitative experimental results demonstrate the robustness and effectiveness of the proposed method.

关键词： image coding visual communication Motion estimation Deep architecture Video compression Feature extraction Robustness

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Seq-Masks: Bridging the gap between appearance and gait modeling for video-based person re-identification

Seq-Masks: Bridging the gap between appearance and gait mode...

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IEEE visual communications and image processing (VCIP)

作者： Zhigang Chang Zhao Yang Yongbiao Chen Qin Zhou Shibao Zheng Institute of Image Processing and Network Engineering Shanghai Jiao Tong University Shanghai China School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781728173221

Video-based person re-identification (Re-ID) aims to match person images in video sequences captured by disjoint surveillance cameras. Traditional video-based person Re-ID methods focus on exploring appearance information, thus, vulnerable against illumination changes, scene noises, camera parameters, and especially clothes/carrying variations. Gait recognition provides an implicit biometric solution to alleviate the above headache. Nonetheless, it experiences severe performance degeneration as camera view varies. In an attempt to address these problems, in this paper, we propose a framework that utilizes the sequence masks (SeqMasks) in the video to integrate appearance information and gait modeling in a close fashion. Specifically, to sufficiently validate the effectiveness of our method, we build a novel dataset named MaskMARS based on MARS. Comprehensive experiments on our proposed large wild video Re-ID dataset MaskMARS evidenced our extraordinary performance and generalization capability. Validations on the gait recognition metric CASIA-B dataset further demonstrated the capability of our hybrid model. Our codes and dataset MaskMARS will be open-sourced as a strong baseline.

关键词： Measurement Mars image recognition Codes visual communication Surveillance Video sequences

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