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检索条件"任意字段=Conference on Visual Communications and Image Processing"

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Texture modeling and classification in wavelet feature space

Texture modeling and classification in wavelet feature space

引用

IEEE International conference on image processing

作者： M.N. Shirazi H. Noda N. Takao Communications Research Laboratories Kobe Japan Kyushu Institute of Technology Kitakyushu Japan

ISBN: (纸本)0780362977

One difficulty of texture analysis and classification in the past was the lack of adequate tools to characterize textures over different scales. Previous developments in multiresolution analysis, such as the wavelet transform, promise ways to overcome this difficulty. We present a texture classification algorithm based on Markov modeling of intrascale and interscale statistical regularities of textures in the wavelet domain. The model provides an accurate multiscale texture representation and underlies a classification algorithm with a high classification rate.

关键词： Wavelet transforms Frequency Classification algorithms Wavelet analysis Statistical distributions Wavelet packets Multiresolution analysis Wavelet domain visual system Face recognition

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Optical Flow in Dynamic Graph Cuts

Optical Flow in Dynamic Graph Cuts

引用

IEEE Pacific Rim conference on communications, Computers and Signal processing

作者： Nurul Arif Setiawan Dhi Aurrahman Chil Woo Lee School of Electronics and Computer Engineering Chonnam National University Gwangju South Korea

ISBN: (纸本)1424411890

In this paper, we propose an approach to calculate optical flow by using dynamic graph cuts framework. We use several good ingredients to estimate optical flow. We combine occlusion model for visual correspondence problem (V. Kolmogorov and R. Zabih, 2001) and illumination invariant optical flow (D. Freedman and M.W. Turek, 2005) to achieve robustness given large occlusion and illumination changes. And we make use the dynamic algorithm from (P. Kohli and P.H.S. Torr, 2005) to estimates dynamically changing MRF models of labeling problems in computer vision. The dynamic algorithm is shown faster than standard counterpart, thus promising real time application of graph cuts techniques to estimate optical flow.

关键词： image motion analysis Optical sensors Lighting Heuristic algorithms Brightness Optical computing Pixel Robustness Computer vision Labeling

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A Modified Algorithm of visual Quality Providing in Lossy Compression of Remote Sensing images

A Modified Algorithm of Visual Quality Providing in Lossy Co...

引用

International conference on Radio Electronics & Info communications (UkrMiCo)

作者： Fangfang Li Sergey Krivenko Vladimir Lukin National Aerospace University- KhAI Kharkiv Ukraine

The development of remote sensing technology leads to a huge number of acquired images needed to be stored and/or transferred. Lossy compression is an essential mean to reduce the image size and, thus, to improve the efficiency of storing and transferring. Meanwhile, a certain quality (including visual quality) must be provided in lossy compression since this quality determines the efficiency of further image processing and/or analysis. However, the task to provide a desired quality in lossy image compression quickly and accurately is not trivial. In this paper, we propose a modified lossy compression scheme able to guarantee a desired quality with high accuracy in two steps. The quality is evaluated in terms of both a conventional metric PSNR and a human visual system (HVS)-based metric PSNR-HVS-M. The experiments are conducted for discrete cosine transform (DCT)-based AGU coder for which we reach the max variance of errors equal to 0.124 dB 2 , and the biases less than 0.27 dB. This result proves that the average rate-distortion curve drawn from the remote sensing category better fits remote sensing data. The combination scheme of derivative and tangent gives better parameter predictions and helps reduce the final error.

关键词： Measurement visualization Technological innovation image coding Rate-distortion visual systems Prediction algorithms

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An efficient video classification system based on HMM in compressed domain

An efficient video classification system based on HMM in com...

引用

International conference on Information, communications and Signal processing

作者： Yi Haoran D. Rajan Chia Liang-Tien Center for Multimedia and Network Technology School of Computer Engineering Nanyang Technological University Singapore

ISBN: (纸本)0780381858

In this paper, we present our method for effective and efficient classification of different types of video that make use of the low level visual features, color and motion features. The color features, similar to the MPEG-7 scalable color descriptors, are the compressed color histograms extracted from the DC images of the video sequences. The motion features, similar to MPEG-7 motion activity descriptors, are extracted from the motion vectors. Both features are extracted from the compressed domain and give a good characterization of the video in both the spatial and temporal dimension. We then classify different types of video using hidden Markov model. First, we train the hidden Markov model for each type of video. Then the trained HMMs are used to classify incoming videos using maximum likelihood classification.

关键词： Video compression Hidden Markov models image coding MPEG 7 Standard Histograms Feature extraction Pattern classification Intelligent networks Computer networks Video sequences

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Development of a VS ultrasound diagnostic system with image evaluation functions

Development of a VS ultrasound diagnostic system with image ...

引用

IEEE Global conference on Consumer Electronics (GCCE)

作者： Jiayi Zhou Norihiro Koizumi Yu Nishiyama Ryosuke Tsumura Hiroyuki Tsukihara Naoki Matsumoto Department of Mechanical and Intelligent Systems The University of Electro-Communications Tokyo Japan Department of Computer and Network Engineering The University of Electro-Communications Tokyo Japan Health and Medical Research Institute National Institute of Advanced Industrial Science and Technology Tokyo Japan Graduate School of Engineering The University of Tokyo Tokyo Japan Department of Gastroenterology and Hepatology Nihon University Tokyo Japan

ISBN: (纸本)9781665492331

An inevitable feature of ultrasound-based diagnoses is that the quality of the ultrasound images produced depends directly on the skill of the physician operating the probe. This is because physicians have to constantly adjust the probe position to obtain a cross-section of the target organ, which is constantly shifting due to patient respiratory motions. Therefore, we developed an ultrasound diagnostic robot that works in cooperation with a visual servo system based on deep learning that will help alleviate the burdens imposed on physicians. Two different image processing methods (BiSeNet V2) were used to detect the target kidney location, as well as to evaluate the appropriateness of the obtained ultrasound images (ResNet 50) in developed system.

关键词： Deep learning visualization Ultrasonic imaging image processing Medical services Probes Servomotors

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Deep Blind Video Quality Assessment for User Generated Videos

Deep Blind Video Quality Assessment for User Generated Video...

引用

IEEE visual communications and image processing (VCIP)

作者： Jiapeng Tang Yu Dong Rong Xie Xiao Gu Li Song Lin Li Bing Zhou Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai China MIGU Co. Ltd Beijing China

ISBN: (数字)9781728180687

ISBN: (纸本)9781728180694

As short video industry grows up, quality assessment of user generated videos has become a hot issue. Existing no reference video quality assessment methods are not suitable for this type of application scenario since they are aimed at synthetic videos. In this paper, we propose a novel deep blind quality assessment model for user generated videos according to content variety and temporal memory effect. Content-aware features of frames are extracted through deep neural network, and a patch-based method is adopted to obtain frame quality score. Moreover, we propose a temporal memory-based pooling model considering temporal memory effect to predict video quality. Experimental results conducted on KoNViD-1k and LIVE-VQC databases demonstrate that the performance of our proposed method outperforms other state-of-the-art ones, and the comparative analysis proves the efficiency o f our temporal pooling model.

关键词： Feature extraction Quality assessment Video recording Streaming media Databases Adaptation models Kernel

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Energy-Efficient Video Streaming: A Study on Bit Depth and Color Subsampling

Energy-Efficient Video Streaming: A Study on Bit Depth and C...

引用

IEEE visual communications and image processing (VCIP)

作者： Hadi Amirpour Lingfeng Qu Jong Hwan Ko Cosmin Stejerean Christian Timmerer Christian Doppler Laboratory ATHENA Alpen-Adria-Universitat Klagenfurt Austria Cyberspace Institute of Advanced Technology Guangzhou University Guangzhou China Department of Electrical and Computer Engineering Sungkyunkwan University South Korea Meta Platforms Inc. Menlo Park USA

ISBN: (数字)9798331529543

ISBN: (纸本)9798331529550

As video dimensions – including resolution, frame rate, and bit depth – increase, a larger bitrate is required to maintain a higher Quality of Experience (QoE). While videos are often optimized for resolution and frame rate to improve compression and energy efficiency, the impact of color space is often overlooked. Larger color spaces are essential for avoiding color banding and delivering High Dynamic Range (HDR) content with richer, more accurate colors, although this comes at the cost of higher processing energy. This paper investigates the effects of bit depth and color subsampling on video compression efficiency and energy consumption. By analyzing different bit depths and subsampling schemes, we aim to determine optimized settings that balance compression efficiency with energy consumption, ultimately contributing to more sustainable and high-quality video delivery. We evaluate both encoding and decoding energy consumption and assess the quality of videos using various metrics including PSNR, VMAF, ColorVideoVDP, and CAMBI. Our findings offer valuable insights for video codec developers and content providers aiming to improve the performance and environmental footprint of their video streaming services.

关键词： Energy consumption image coding image color analysis Energy resolution Bit rate Color Streaming media Energy efficiency Decoding Quality of experience

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A point cloud compression framework via spherical projection

A point cloud compression framework via spherical projection

引用

IEEE visual communications and image processing (VCIP)

作者： Yingshen He Ge Li Yiting Shao Jing Wang Yueru Chen Shan Liu Peking University Shenzhen Graduate School Shenzhen China Peng Cheng Lboratory Shenzhen China Media Lab Tencent America Palo Alto USA

ISBN: (数字)9781728180687

ISBN: (纸本)9781728180694

In this paper, we propose a sphere-projection-based framework for point cloud geometry and attribute lossless and lossy coding. The original point cloud is adaptively divided into blocks, and then we create a fitting sphere in each block for modeling the local geometry structure of the point cloud. Sphere coordination transform and spherical projection scheme are introduced to transfer a 3D point cloud to a set of the range images. A novel compact representation of generated range images based on Morton codes is proposed to separate the range images into occupancy images and attributes vectors for further compression. Experimental results demonstrate that for the LiDAR point clouds datasets in lossless compression, the proposed method offers better performance than geometry-based point cloud compression (G-PCC). For the object point clouds datasets in lossy compression, the proposed method has better rate-distortion (R-D) performance than Draco.

关键词： Three-dimensional displays image coding Geometry Laser radar Tools Transform coding Codecs

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A Theory of Occlusion for Improving Rendering Quality of Views

A Theory of Occlusion for Improving Rendering Quality of Vie...

引用

IEEE visual communications and image processing (VCIP)

作者： Yijun Zeng Weiyan Chen Mengqin Bai Yangdong Zeng Changjian Zhu School of Electron. Engineering Guangxi Normal Univ. Guilin China Guilin Medical University Guilin Guilin China

ISBN: (数字)9781728180687

ISBN: (纸本)9781728180694

Occlusion lack compensation (OLC) is a multiplexing gain optimization data acquisition and novel views rendering strategy for light field rendering (LFR). While the achieved OLC is much higher than previously thought possible, the improvement comes at the cost of requiring more scene information. This can capture more detailed scene information, including geometric information, texture information and depth information, by learning and training methods. In this paper, we develop an occlusion compensation (OCC) model based on restricted boltzmann machine (RBM) to compensate for lack scene information caused by occlusion. We show that occlusion will cause the lack of captured scene information, which will lead to the decline of view rendering quality. The OCC model can estimate and compensate the lack information of occlusion edge by learning. We present experimental results to demonstrate the performance of OCC model with analog training, verify our theoretical analysis, and extend our conclusions on optimal rendering quality of light field.

关键词： Cameras Rendering (computer graphics) Bandwidth Mathematical model Two dimensional displays Three-dimensional displays Signal processing

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Prediction-Aware Quality Enhancement of VVC Using CNN

Prediction-Aware Quality Enhancement of VVC Using CNN

引用

IEEE visual communications and image processing (VCIP)

作者： Fatemeh Nasiri Wassim Hamidouche Luce Morin Nicolas Dhollande Gildas Cocherel IRT b<>com France CNRS IETR - UMR 6164 Univ Rennes INSA Rennes Rennes France AVIWEST France

ISBN: (数字)9781728180687

ISBN: (纸本)9781728180694

The upcoming video coding standard, Versatile Video Coding (VVC), has shown great improvement compared to its predecessor, High Efficiency Video Coding (HEVC), in terms of bitrate saving. Despite its substantial performance, compressed videos might still suffer from quality degradation at low bitrates due to coding artifacts such as blockiness, blurriness and ringing. In this work, we exploit Convolutional Neural Networks (CNN) to enhance quality of VVC coded frames after decoding in order to reduce low bitrate artifacts. The main contribution of this work is the use of coding information from the compressed bitstream. More precisely, the prediction information of intra frames is used for training the network in addition to the reconstruction information. The proposed method is applied on both luminance and chrominance components of intra coded frames of VVC. Experiments on VVC Test Model (VTM) show that, both in low and high bitrates, the use of coding information can improve the BD-rate performance by about 1% and 6% for luma and chroma components, respectively.

关键词： Encoding Training Convolutional codes image reconstruction Distortion Streaming media Decoding

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