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检索条件"任意字段=Conference on Visual Communications and Image Processing 2005"

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RDPlot – An Evaluation Tool for Video Coding Simulations

RDPlot – An Evaluation Tool for Video Coding Simulations

引用

IEEE visual communications and image processing (VCIP)

作者： Jens Schneider Johannes Sauer Mathias Wien Institut für Nachrichtentechnik RWTH Aachen University Germany Lehrstuhl für Bildverarbeitung RWTH Aachen University Germany

ISBN: (纸本)9781728173221

RDPlot is an open source GUI application for plotting Rate-Distortion (RD)-curves and calculating Bjøntegaard Delta (BD) statistics [1]. It supports parsing the output of commonly used reference software packages, parsing *.csv-formatted files, and *.xml-formatted files. Once parsed, RDPlot offers the ability to evaluate video coding results interactively. Conceptually, several measures can be plotted over the bitrate and BD measurements can be conducted accordingly. Moreover, plots and corresponding BD statistics can be exported, and directly integrated into LaTeX documents.

关键词： Video coding visual communication Software packages image processing Bit rate Rate-distortion Graphical user interfaces

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No-Reference Stereoscopic image Quality Assessment Considering Binocular Disparity and Fusion Compensation

No-Reference Stereoscopic Image Quality Assessment Consideri...

引用

IEEE visual communications and image processing (VCIP)

作者： Feng Jinhui Sumei Li Yongli Chang Tianjin International Engineering Institute Tianjin University Tianjin China School of Electrical and Information Enginering Tianjin University Tianjin China

ISBN: (纸本)9781728173221

In this paper, we propose an optimized dual stream convolutional neural network (CNN) considering binocular disparity and fusion compensation for no-reference stereoscopic image quality assessment (SIQA). Different from previous methods, we extract both disparity and fusion features from multiple levels to simulate hierarchical processing of the stereoscopic images in human brain. Given that the ocular dominance plays an important role in quality evaluation, the fusion weights assignment module (FWAM) is proposed to assign weight to guide the fusion of the left and the right features respectively. Experimental results on four public stereoscopic image databases show that the proposed method is superior to the state-of-the-art SIQA methods on both symmetrical and asymmetrical distortion stereoscopic images.

关键词： image quality visual communication image databases Stereo image processing Streaming media Feature extraction Distortion

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An intricate spectrogram processing in speech enhancement using machine learning with cloud computing

An intricate spectrogram processing in speech enhancement us...

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International conference on image Information processing

作者： Yenna Geetha Reddy G Mahendran Ameer Al-Khaykan Omar A. Alkawak S. A. Kalaiselvan A. Priya Department of Computer Science and Engineering MAlla Reddy Engineering College for Women (UGC Autonomous)Kompally Secunderabad Telangana India Department of Mechancal Engineering R.M.K Engineering Collegekavaraipettai Chennai Tamil Nadu India Department of Electronic and Communications Engineering University of Kufa Najaf Iraq Department of Air Conditioning and Refrigeration Technical Engineering Al-Mustaqbal University College Hilla Babil Iraq Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Science (SIMATS) Chennai Tamil Nadu India School of Architecture Koneru Lakshmaiah Educational Foundation Guntur Andhra Pradesh India

ISBN: (数字)9798350371406

ISBN: (纸本)9798350371413

The spectrogram is defined as the visual representation of the signal strength with a particular interval of time regarding frequencies in the appropriate waveform. It is demonstrated using the Fourier transform. It is illustrated in a three-dimensional plot of signal composed with amplitude versus frequency and time. They are classified as long signal sections and short signal sections with filters. It demonstrates the consecutive spectacle of the sound signal at a particular interval of time. The time-frequency representation of audio signals is obtained through spectrograms. This helps in the understanding of the speech data. Machine learning plays an important role in the identification of the relevant features in the spectrogram. The intricate patterns in the time and frequency domains are represented through CNN and RNN. These models are trained and tested through a large dataset which includes both clean and noisy speech samples. This helps to learn complex interrelationships and patterns associated with varied environmental conditions and interference systems. The computational demands of these systems are handled through the cloud computing techniques. They provide a platform for effective solutions for performing real-time interference. These cloud services provide various collaborations to numerous models to achieve desired outcomes. The proposed system provides higher adaptability in varied environmental and noisy profiles. Thus the integration of cloud computing with machine learning provides real-time processing with a natural seamless user experience.

关键词： Cloud computing Time-frequency analysis visualization Computational modeling Machine learning Interference Speech enhancement

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Polynomial image-Based Rendering for non-Lambertian Objects

Polynomial Image-Based Rendering for non-Lambertian Objects

引用

IEEE visual communications and image processing (VCIP)

作者： Sarah Fachada Daniele Bonatto Mehrdad Teratani Gauthier Lafruit Laboratory of Image Synthesis and Analysis Université Libre de Bruxelles Brussels Belgium

ISBN: (纸本)9781728173221

Non-Lambertian objects present an aspect which depends on the viewer's position towards the surrounding scene. Contrary to diffuse objects, their features move non-linearly with the camera, preventing rendering them with existing Depth image-Based Rendering (DIBR) approaches, or to triangulate their surface with Structure-from-Motion (SfM). In this paper, we propose an extension of the DIBR paradigm to describe these non-linearities, by replacing the depth maps by more complete multi-channel “non-Lambertian maps”, without attempting a 3D reconstruction of the scene. We provide a study of the importance of each coefficient of the proposed map, measuring the trade-off between visual quality and data volume to optimally render non-Lambertian objects. We compare our method to other state-of-the-art image-based rendering methods and outperform them with promising subjective and objective results on a challenging dataset.

关键词： Surface reconstruction Three-dimensional displays visual communication Volume measurement image processing Rendering (computer graphics) Cameras

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Application of Computer Digital Simulation Technology in the Research of Martial arts Action Structure image 16

Application of Computer Digital Simulation Technology in the...

引用

16th IEEE International Wireless communications and Mobile Computing conference (IEEE IWCMC)

作者： Wang, Qingbao Baicheng Normal Univ Coll Phys Educ Baicheng 137000 Jilin Peoples R China

ISBN: (纸本)9781728131290

The reference of Martial arts action structure to assist the artificial correction is poor, for this problem, in this paper, a new method of Martial arts action structure analysis and reconstruction based on computer numerical simulation is proposed. Firstly, three-dimensional visual image information acquisition of martial arts is carried out, and adaptive threshold decomposition and wavelet analysis are used to perform noise reduction pretreatment. The original domain feature point library is formed by the original separation of the domain feature points of the martial arts action structure image. Then, the edge contour feature extraction method is used to extract the contour features of the martial arts in the image, input into the expert system of the orthodontics, carry on the visual analysis and correction, and realize the Martial arts action structure analysis and the feature reconstruction identification. The results of computer simulation show that this method can be used to reconstruct the martial arts structure and improve the quantitative analysis ability of martial arts. The signal-to-noise ratio of the output image is high, and the recognition performance of the image processing and motion is better.

关键词： computer numerical simulation technology Martial arts sports training structural characteristics action identification

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History-Based MVP (HMVP) for Gradual Decoding Refresh of VVC

History-Based MVP (HMVP) for Gradual Decoding Refresh of VVC

引用

IEEE visual communications and image processing (VCIP)

作者： Limin Wang Seungwook Hong Krit Panusopone Multimedia Technologies Research Nokia San Diego USA

ISBN: (纸本)9781728173221

Versatile Video Coding (VVC) is a new international video coding standard. One of the functionalities that VVC supports is so called Gradual Decoding Refresh (GDR). GDR is mainly for (ultra) low-delay applications. As the latest video coding standard, VVC employs many new and advanced coding tools. Among them is HMVP (History-based Motion Vector Prediction), which however can cause leaks for GDR applications. This paper analyzes the leak problem associated with HMVP for GDR and proposes suggestions on how to use HMVP for GDR applications.

关键词： Video coding image coding visual communication Decoding Standards

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Cross-Block Difference Guided Fast CU Partition for VVC Intra Coding

Cross-Block Difference Guided Fast CU Partition for VVC Intr...

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IEEE visual communications and image processing (VCIP)

作者： Hewei Liu Shuyuan Zhu Ruiqin Xiong Guanghui Liu Bing Zeng University of Electronic Science and Technology of China Chengdu China Peking University Beijing China

ISBN: (纸本)9781728173221

In this paper, we propose a new fast CU partition method for VVC intra coding based on the cross-block difference. This difference is measured by the gradient and the content of sub-blocks obtained from partition and is employed to guide the skipping of unnecessary horizontal and vertical partition modes. With this guidance, a fast determination of block partitions is accordingly achieved. Compared with VVC, our proposed method can save 41.64% (on average) encoding time with only 0.97% (on average) increase of BD-rate.

关键词： image coding visual communication

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Learned Multi-Field De-Interlacing with Feature Alignment via Deformable Residual Convolution Blocks

Learned Multi-Field De-Interlacing with Feature Alignment vi...

引用

IEEE visual communications and image processing (VCIP)

作者： Ronglei Ji A.Murat Tekalp Koc University Istanbul Turkey

ISBN: (纸本)9781728173221

Deinterlacing continues to be an important problem of interest since many digital TV broadcasts and catalog content are still in interlaced format. Although deep learning has had huge impact in all forms of image/video processing, learned deinterlacing has not received much attention in the industry or academia. In this paper, we propose a novel multi-field deinterlacing network that aligns features from adjacent fields to a reference field (to be deinterlaced) using deformable residual convolution blocks. To the best of our knowledge, this paper is the first to propose fusion of multi-field features that are aligned via deformable convolutions for deinterlacing. We demonstrate through extensive experimental results that the proposed method provides state-of-the-art deinterlacing results in terms of both PSNR and perceptual quality.

关键词： Industries Deep learning Convolution visual communication image processing Digital TV

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SA(2,R) Multi-scale contour registration based on EM Algorithm

SA(2,R) Multi-scale contour registration based on EM Algorit...

引用

IEEE visual communications and image processing (VCIP)

作者： Khaoula Sakrani Sinda Elghoul Sarra Falleh Faouzi Ghorbel CRISTAL Laboratory GRIFT Research Group National School of Computer Science (ENSI) Manouba Tunisia

ISBN: (纸本)9781728173221

Here we propose a novel affine registration method for planar curves. It is based on a pseudo-inverse algorithm applied to the source and target curves in their multi-scale version. The proposed registration system selects the relevant scales in the optimized L 2 distances. The retrieved smoothing parameters are realized with the Gaussian Expectation-Maximization (EM) algorithm. We resolve the global system, formed by equations corresponding to EM selected scales.

关键词： Linear systems Smoothing methods image recognition visual communication Robot sensing systems Complexity theory Remote sensing

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ARITM: A Perceptual Quality Magnification of Noise Suppressed Digital images using Adaptive Recursion and image Transformation Model

ARITM: A Perceptual Quality Magnification of Noise Suppresse...

引用

Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), International conference on

作者： K. Kannan G. Divya L. Chithra V. Aruna V. Mohanavel Department of ECE R.M.K. College of Engineering and Technology Puduvoyal Chennai Department of Networking and Communications Faculty of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai India Department of ECE S.A.Engineering College Chennai Department of ECE Panimalar Engineering College Chennai Centre for Materials Engineering and Regenerative Medicine Bharath Institute of Higher Education and Research Chennai Tamil Nadu India Department of Mechanical Engineering Chandigarh University Mohali Punjab India

In the realm of digital image processing and enhancement, the relentless pursuit of achieving higher perceptual quality in noise-suppressed images has remained a compelling challenge. This abstract presents a novel approach that leverages the synergy between adaptive recursion and a sophisticated image transformation model to magnify the perceptual quality of noise-suppressed digital images. The proliferation of digital imagery in various applications, from medical diagnostics to multimedia content, necessitates the development of advanced techniques to preserve and enhance image fidelity. While noise suppression techniques have made significant strides in reducing unwanted artifacts, they often introduce trade-offs between noise reduction and preservation of image details. Our proposed method begins by employing adaptive recursion, where the image is divided into local regions, each analyzed independently for noise characteristics and visual features. Adaptive recursion ensures that noise reduction is applied selectively, preserving important image details, even in challenging scenarios. The synergy between adaptive recursion and the image transformation model is a key highlight of our approach. By iteratively applying the transformation model within each local region, we adaptively enhance image features that contribute to perceptual quality, such as sharpness, contrast, and color fidelity. This adaptive enhancement process ensures that image details are magnified while suppressing noise artifacts, ultimately resulting in images of superior perceptual quality. Our experimental results, conducted on diverse datasets with various levels of noise, demonstrate significant improvements in perceptual quality compared to state-of-the-art methods. Additionally, we evaluate the computational efficiency of our approach, highlighting its feasibility for real-time and high-throughput image enhancement applications.

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