- 标题
- 摘要
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- 实验方案
- 产品
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Real time video image enhancement approach using particle swarm optimisation technique with adaptive cumulative distribution function based histogram equalization
摘要： Recent years, real time videos are playing an important role in different applications such as pattern recognition, security purpose, news analysis, weather digest, and video browser and so on. Due to the importance of real time video applications, the quality of the real time video must be improved for making effective results in real time video analysis process. This paper introduces the particle optimization with adaptive cumulative distribution based histogram enhancement technique (PACDHE) for improving the real time video quality. Initially the videos are collected, each incoming frame has been analyzed and noise present in the video frame is eliminated by applying the non-divisional median filter. After that, quality of real time video is enhanced iteratively by examining each pixel present in video frames using the optimized fitness and cumulative distribution function. This process is repeated continuously until to enhance the real time video frames contrast and quality. Then the performance of the system is analyzed by using CV online video database and the efficiency is examined in terms of peak signal to noise ratio (PSNR), Absolute Mean Brightness Error (AMBE) and Entropy. The experimental results of PSO are compared with genetic algorithm based approach and found that PSO outperforms the GA approach and the existing histogram equalization approach and the existing histogram equalization approaches.
关键词： contrast enhancement,particle optimization based adaptive cumulative distribution based histogram enhancement technique (PACDHE),fitness and cumulative distribution function,CV online video database,Video quality
更新于2025-09-23 15:23:52
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[IEEE 2018 25th IEEE International Conference on Image Processing (ICIP) - Athens, Greece (2018.10.7-2018.10.10)] 2018 25th IEEE International Conference on Image Processing (ICIP) - Large Scale Subjective Video Quality Study
摘要： Most of today’s video quality assessment (VQA) databases contain very limited content and distortion diversities and fail to adequately represent real world video impairments. This is in part because conducting subjective studies in the lab is slow, inefficient and expensive process. Crowdsourcing quality scores is a more scalable solution. However given that viewers operate under innumerable viewing conditions (including display resolutions, viewing distances, internet connection speeds) and because they are not closely supervised, multiple technical challenges arise. We carefully designed a framework in Amazon Mechanical Turk (AMT) to address the many technical issues that are faced. We launched the largest available VQA study, collecting more than 205000 opinion scores provided by more than 4700 unique participants. We have verified that our framework provided us with results that are highly consistent with the ones obtained in a lab environment under controlled conditions.
关键词： Subjective Study,Video Quality Assessment,Crowdsourcing
更新于2025-09-23 15:21:01
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Modelling, Simulation, and Performance Analysis of a Microgrid with Photovoltaic Energy for Eastern Region of Saudi Arabia
摘要： We announce a new video quality model (VQM) that accounts for the perceptual impact of variable frame delays (VFD) in videos with demonstrated top performance on the laboratory for image and video engineering (LIVE) mobile video quality assessment (VQA) database. This model, called VQM_VFD, uses perceptual features extracted from spatial-temporal blocks spanning fixed angular extents and a long edge detection filter. VQM_VFD predicts video quality by measuring multiple frame delays using perception based parameters to track subjective quality over time. In the performance analysis of VQM_VFD, we evaluated its efficacy at predicting human opinions of visual quality. A detailed correlation analysis and statistical hypothesis testing show that VQM_VFD accurately predicts human subjective judgments and substantially outperforms top-performing image quality assessment and VQA models previously tested on the LIVE mobile VQA database. VQM_VFD achieved the best performance on the mobile and tablet studies of the LIVE mobile VQA database for simulated compression, wireless packet-loss, and rate adaptation, but not for temporal dynamics. These results validate the new model and warrant a hard release of the VQM_VFD algorithm. It is freely available for any purpose, commercial, or noncommercial at http://www.its.bldrdoc.gov/vqm/.
关键词： Edge detection,VQM_VFD,video quality model,video quality database,variable frame delay,video quality assessment
更新于2025-09-23 15:19:57
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Analysis for an Improved Nanomechanical Microcantilever Sensor on Optical Waveguides
摘要： We announce a new video quality model (VQM) that accounts for the perceptual impact of variable frame delays (VFD) in videos with demonstrated top performance on the laboratory for image and video engineering (LIVE) mobile video quality assessment (VQA) database. This model, called VQM_VFD, uses perceptual features extracted from spatial-temporal blocks spanning fixed angular extents and a long edge detection filter. VQM_VFD predicts video quality by measuring multiple frame delays using perception based parameters to track subjective quality over time. In the performance analysis of VQM_VFD, we evaluated its efficacy at predicting human opinions of visual quality. A detailed correlation analysis and statistical hypothesis testing show that VQM_VFD accurately predicts human subjective judgments and substantially outperforms top-performing image quality assessment and VQA models previously tested on the LIVE mobile VQA database. VQM_VFD achieved the best performance on the mobile and tablet studies of the LIVE mobile VQA database for simulated compression, wireless packet-loss, and rate adaptation, but not for temporal dynamics. These results validate the new model and warrant a hard release of the VQM_VFD algorithm. It is freely available for any purpose, commercial, or noncommercial at http://www.its.bldrdoc.gov/vqm/.
关键词： Edge detection,video quality model,video quality assessment,video quality database,variable frame delay,VQM_VFD
更新于2025-09-19 17:13:59
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Synchronous 2D/3D Switching System for Service-Compatible 3DTV Broadcasting
摘要： This paper proposes a new broadcasting system for the service-compatible 3DTV in which the 3D service can coexist with the conventional digital TV broadcast. In the proposed system, the commercial 3DTV service can be implemented via the existing DTV channel without utilizing the dedicated 3DTV system. This 2D/3D system interworks with the conventional system and can switch to 2D or 3D service according to the broadcast programming and schedule. The system also provides a mechanism that can prevent the synchronization mismatch between left and right video streams and between the stream and the associated signaling in the 2D/3D transition periods. The picture quality measurements are carried out based on the ITU-R recommended test to check the level of quality of service provided by the proposed scheme. The conformity tests are also performed with the conventional channel and the receiver for the DTV system to confirm the feasibility of the proposed one for the commercial service.
关键词： 3DTV,video quality,service-compatible,3D multiplexer,2D/3D switch
更新于2025-09-10 09:29:36
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PeQASO: Perceptual Quality Assessment of Streamed Videos Using Optical Flow Features
摘要： In this paper, we introduce PeQASO, a perceptual quality assessment framework for streamed videos using optical ?ow features. This approach is a reduced-reference pixel-based and relies only on the deviation of the optical ?ow of the corrupted frames. This technique compares an optical ?ow descriptor from the received frame against the descriptor obtained from the anchor frame. This approach is suitable for videos with complex motion patterns. Our technique does not make any assumptions on the coding conditions, network loss patterns or error concealment techniques. In this paper, we consider both sources of artifacts and distortions in streaming, including compression artifacts. We validate our proposed metric by testing it on a variety of distorted sequences from three proposed and commonly utilized video quality assessment databases. Our results show that our metric estimates the perceptual quality at the sequence level accurately. We report the correlation coef?cients with the differential mean opinion scores reported in the database. For compression artifacts, the results show Spearman’s and Pearson’s correlations of 0.96 and 0.94 for all the tested sequences, respectively. For channel-induced distortion, the results show Spearman’s and Pearson’s correlations of 0.88 and 0.89, respectively. For all other distortions, the average Spearman’s and Pearson’s correlations are 0.82 and 0.79, respectively.
关键词： Video quality assessment,optical ?ow,video streaming,video coding,channel losses,video quality monitoring,video distortion
更新于2025-09-09 09:28:46
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[IEEE 2018 25th IEEE International Conference on Image Processing (ICIP) - Athens, Greece (2018.10.7-2018.10.10)] 2018 25th IEEE International Conference on Image Processing (ICIP) - Only-Reference Video Quality Assessment for Video Coding Using Convolutional Neural Network
摘要： Conventional video quality assessment methods are either full-, reduced-, or no-reference methods that need to access decoded videos. Hence, to calculate quality of decoded video in video coding regarding an image/video quality metric, complete encoding and decoding have to executed, which is computationally expensive. To address this problem, we propose to estimate quality of decoded videos from the original video only (i.e., only-reference) using convolutional neural network, as if the original video is encoded using a range of quantization parameter. The proposed network is shallow and can be trained to estimate various video quality metrics. Furthermore, among potential rate control applications using the proposed network, we demonstrate achieving a targeted decoded-video quality by selecting a proper quantization parameter before actually encoding.
关键词： only-reference,Video quality assessment,convolutional neural network,video coding
更新于2025-09-09 09:28:46