Image Quality and System Performance最新文献

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Front Matter: Volume 9396 封面:第9396卷
Image Quality and System Performance Pub Date : 1900-01-01 DOI: 10.1117/12.2185155
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引用次数: 1
GPGPU based implementation of a high performing No Reference (NR) - IQA algorithm, BLIINDS-II 基于GPGPU的高性能无参考(NR) - IQA算法blinds - ii的实现
Image Quality and System Performance Pub Date : 1900-01-01 DOI: 10.2352/ISSN.2470-1173.2017.12.IQSP-220
Aman Yadav, S. Sohoni, D. Chandler
{"title":"GPGPU based implementation of a high performing No Reference (NR) - IQA algorithm, BLIINDS-II","authors":"Aman Yadav, S. Sohoni, D. Chandler","doi":"10.2352/ISSN.2470-1173.2017.12.IQSP-220","DOIUrl":"https://doi.org/10.2352/ISSN.2470-1173.2017.12.IQSP-220","url":null,"abstract":"A relatively recent thrust in IQA research has focused on estimating the quality of a distorted image without access to the original (reference) image. Algorithms for this so-called noreference IQA (NR IQA) have made great strides over the last several years, with some NR algorithms rivaling full-reference algorithms in terms of prediction accuracy. However, there still remains a large gap in terms of runtime performance; NR algorithms remain significantly slower than FR algorithms, owing largely to their reliance on natural-scene statistics and other ensemble-based computations. To address this issue, this paper presents a GPGPU implementation, using NVidia’s CUDA platform, of the popular Blind Image Integrity Notator using DCT Statistics (BLIINDS-II) algorithm [8], a state of the art NR-IQA algorithm. We copied the image over to the GPU and performed the DCT and the statistical modeling using the GPU. These operations, for each 5x5 pixel window, are executed in parallel. We evaluated the implementation by using NVidia Visual Profiler, and we compared the implementation to a previously optimized CPU C++ implementation. By employing suitable optimizations on code, we were able to reduce the runtime for each 512x512 image from approximately 270 ms down to approximately 9 ms, which includes the time for all data transfers across PCIe bus. We discuss our unique implementation of BLIINDS-II designed specifically for use on the GPU, the insights gained from the runtime analyses, and how the GPGPU techniques developed here can be adapted for use in other NR IQA algorithms. Introduction Effective and efficient quality assessment of visual content finds application in a plenty of areas ranging from quality monitoring of video delivery systems, comparison of compression techniques to image reconstruction. Unfortunately, the benefits of recent advances in IQA and VQA have not carried over to real world systems owing largely to long execution time of these algorithms even for a single frame of image as has been pointed out in multiple publications [1][2][3][9] in the past. GPGPU based implementation for three different Full Reference IQA algorithms have been presented in [4], [5] and [6] with varying success. In time sensitive applications like quality of service monitoring in live broadcasting and video conferencing, a fast performing No Reference IQA is very essential. Addressing this strong need [7] for real time No Reference IQA, we apply GPGPU techniques to a high performing No Reference IQA algorithm, BLIINDS-II. The objective of our project is to utilize the data parallelism in BLIINDS-II NR-IQA by implementing it using a GPGPU. We aim to study the compute resources and the memory bandwidth needed along with latency issues following the data access pattern of the algorithm and propose suitable optimization techniques. Overview of BLIINDS-II algorithm BLIINDS-II is a Non Distortion Specific Natural Scene Statistics (NSS) based NR-IQA. NSS models are t","PeriodicalId":274168,"journal":{"name":"Image Quality and System Performance","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131487459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Estimation of ISO12233 Edge Spatial Frequency Response from Natural Scene Derived Step-Edge Data 基于自然场景阶跃边缘数据的ISO12233边缘空间频率响应估计
Image Quality and System Performance Pub Date : 1900-01-01 DOI: 10.2352/j.imagingsci.technol.2021.65.6.060402
O. V. Zwanenberg, S. Triantaphillidou, R. Jenkin, A. Psarrou
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引用次数: 2
Objective image quality evaluation of HDR videos captured by smartphones 智能手机拍摄HDR视频的客观图像质量评价
Image Quality and System Performance Pub Date : 1900-01-01 DOI: 10.2352/EI.2022.34.9.IQSP-312
Cyril Lajarge, François-Xavier Thomas, Elodie Souksava, L. Chanas, Hoang-Phi Nguyen, F. Guichard
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引用次数: 0
A continuous bitstream-based blind video quality assessment using multi-layer perceptron 基于多层感知器的连续比特流盲视频质量评估
Image Quality and System Performance Pub Date : 1900-01-01 DOI: 10.2352/EI.2022.34.9.IQSP-319
Hugo Merly, A. Ninassi, C. Charrier
{"title":"A continuous bitstream-based blind video quality assessment using multi-layer perceptron","authors":"Hugo Merly, A. Ninassi, C. Charrier","doi":"10.2352/EI.2022.34.9.IQSP-319","DOIUrl":"https://doi.org/10.2352/EI.2022.34.9.IQSP-319","url":null,"abstract":"","PeriodicalId":274168,"journal":{"name":"Image Quality and System Performance","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114613399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Multi-gene Genetic Programming based Predictive Models for Full-reference Image Quality Assessment 基于多基因遗传规划的全参考图像质量评估预测模型
Image Quality and System Performance Pub Date : 1900-01-01 DOI: 10.2352/j.imagingsci.technol.2021.65.6.060409
Naima Merzougui, L. Djerou
{"title":"Multi-gene Genetic Programming based Predictive Models for Full-reference Image Quality Assessment","authors":"Naima Merzougui, L. Djerou","doi":"10.2352/j.imagingsci.technol.2021.65.6.060409","DOIUrl":"https://doi.org/10.2352/j.imagingsci.technol.2021.65.6.060409","url":null,"abstract":"\u0000 Many objective quality metrics for assessing the visual quality of images have been developed during the last decade. A simple way to fine tune the efficiency of assessment is through permutation and combination of these metrics. The goal of this fusion approach is to take advantage of the metrics utilized and minimize the influence of their drawbacks. In this paper, a symbolic regression technique using an evolutionary algorithm known as multi-gene genetic programming (MGGP) is applied for predicting subject scores of images in datasets using a combination of objective scores of a set of image quality metrics (IQM). By learning from image datasets, the MGGP algorithm can determine appropriate image quality metrics, from 21 metrics utilized, whose objective scores employed as predictors in the symbolic regression model, by optimizing simultaneously two competing objectives of model ‘goodness of fit’ to data and model ‘complexity’. Six large image databases (namely LIVE, CSIQ, TID2008, TID2013, IVC and MDID) that are available in public domain are used for learning and testing the predictive models, according the k-fold-cross-validation and the cross dataset strategies. The proposed approach is compared against state-of-the-art objective image quality assessment approaches. Results of comparison reveal that the proposed approach outperforms other state-of-the-art recently developed fusion approaches.\u0000","PeriodicalId":274168,"journal":{"name":"Image Quality and System Performance","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133225866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Quality-based Video Bitrate Control for WebRTC-based Teleconference Services 基于webbrtc的电话会议服务的视频比特率控制
Image Quality and System Performance Pub Date : 1900-01-01 DOI: 10.2352/EI.2022.34.9.IQSP-333
M. Yokota, Kazuhisa Yamagishi
{"title":"Quality-based Video Bitrate Control for WebRTC-based Teleconference Services","authors":"M. Yokota, Kazuhisa Yamagishi","doi":"10.2352/EI.2022.34.9.IQSP-333","DOIUrl":"https://doi.org/10.2352/EI.2022.34.9.IQSP-333","url":null,"abstract":"","PeriodicalId":274168,"journal":{"name":"Image Quality and System Performance","volume":"169 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114380746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
New visual noise measurement on a versatile laboratory setup in HDR conditions for smartphone camera testing 在HDR条件下智能手机相机测试的多功能实验室设置上的新视觉噪声测量
Image Quality and System Performance Pub Date : 1900-01-01 DOI: 10.2352/EI.2022.34.9.IQSP-313
Thomas Bourbon, Coraline S. Hillairet, Benoit Pochon, F. Guichard
{"title":"New visual noise measurement on a versatile laboratory setup in HDR conditions for smartphone camera testing","authors":"Thomas Bourbon, Coraline S. Hillairet, Benoit Pochon, F. Guichard","doi":"10.2352/EI.2022.34.9.IQSP-313","DOIUrl":"https://doi.org/10.2352/EI.2022.34.9.IQSP-313","url":null,"abstract":"","PeriodicalId":274168,"journal":{"name":"Image Quality and System Performance","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121216625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Exploration of comfort factors for virtual reality environments 虚拟现实环境中舒适因素的探索
Image Quality and System Performance Pub Date : 1900-01-01 DOI: 10.2352/EI.2022.34.9.IQSP-393
Thibault Lacharme, M. Larabi, Daniel Méneveaux
{"title":"Exploration of comfort factors for virtual reality environments","authors":"Thibault Lacharme, M. Larabi, Daniel Méneveaux","doi":"10.2352/EI.2022.34.9.IQSP-393","DOIUrl":"https://doi.org/10.2352/EI.2022.34.9.IQSP-393","url":null,"abstract":"","PeriodicalId":274168,"journal":{"name":"Image Quality and System Performance","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116126349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Image enhancement dataset for evaluation of image quality metrics 用于评估图像质量指标的图像增强数据集
Image Quality and System Performance Pub Date : 1900-01-01 DOI: 10.2352/EI.2022.34.9.IQSP-317
Altynay Kadyrova, Marius Pedersen, Bilal Ahmad, Dipendra J. Mandal, Mathieu Nguyen, Pauline Hardeberg Zimmermann
{"title":"Image enhancement dataset for evaluation of image quality metrics","authors":"Altynay Kadyrova, Marius Pedersen, Bilal Ahmad, Dipendra J. Mandal, Mathieu Nguyen, Pauline Hardeberg Zimmermann","doi":"10.2352/EI.2022.34.9.IQSP-317","DOIUrl":"https://doi.org/10.2352/EI.2022.34.9.IQSP-317","url":null,"abstract":"","PeriodicalId":274168,"journal":{"name":"Image Quality and System Performance","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116739071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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