No-reference video quality assessment in the compressed domain
IEEE Transactions on Consumer Electronics, 2012In this paper, a novel no-reference video quality assessment algorithm in the compressed domain is introduced. The proposed algorithm takes into account of three key factors; the quantization parameter, the motion, and the bit allocation factor which are calculated using the information extracted from the compressed bitstream.
Xiangyu Lin +3 more
exaly +2 more sources
CVD2014—A Database for Evaluating No-Reference Video Quality Assessment Algorithms
IEEE Transactions on Image Processing, 2016In this paper, we present a new video database: CVD2014-Camera Video Database. In contrast to previous video databases, this database uses real cameras rather than introducing distortions via post-processing, which results in a complex distortion space in regard to the video acquisition process.
Toni Ilkka Olavi Virtanen +2 more
exaly +5 more sources
An Efficient Method for No-Reference Video Quality Assessment [PDF]
Journal of Imaging, 2021 Methods for No-Reference Video Quality Assessment (NR-VQA) of consumer-produced video content are largely investigated due to the spread of databases containing videos affected by natural distortions.
Mirko Agarla +2 more
doaj +7 more sources
No-Reference Video Quality Assessment Using the Temporal Statistics of Global and Local Image Features [PDF]
Sensors, 2022 During acquisition, storage, and transmission, the quality of digital videos degrades significantly. Low-quality videos lead to the failure of many computer vision applications, such as object tracking or detection, intelligent surveillance, etc.
Domonkos Varga
doaj +4 more sources
Reduced reference image and video quality assessments: review of methods [PDF]
EURASIP Journal on Image and Video Processing, 2022 With the growing demand for image and video-based applications, the requirements of consistent quality assessment metrics of image and video have increased.
Shahi Dost +5 more
doaj +4 more sources
No-Reference Video Quality Assessment Using Multi-Pooled, Saliency Weighted Deep Features and Decision Fusion [PDF]
Sensors, 2022 With the constantly growing popularity of video-based services and applications, no-reference video quality assessment (NR-VQA) has become a very hot research topic.
Domonkos Varga
doaj +2 more sources
Video Quality Analysis: Steps towards Unifying Full and No Reference Cases
Standards, 2022 Video quality assessment (VQA) is now a fast-growing field, maturing in the full reference (FR) case, yet challenging in the exploding no reference (NR) case.
Pankaj Topiwala +4 more
doaj +3 more sources
KonVid-150k: A Dataset for No-Reference Video Quality Assessment of Videos in-the-Wild
IEEE Access, 2021 Video quality assessment (VQA) methods focus on particular degradation types, usually artificially induced on a small set of reference videos. Hence, most traditional VQA methods under-perform in-the-wild.
Franz Gotz-Hahn +3 more
doaj +6 more sources
No-Reference Quality Assessment of In-Capture Distorted Videos [PDF]
Journal of Imaging, 2020 We introduce a no-reference method for the assessment of the quality of videos affected by in-capture distortions due to camera hardware and processing software. The proposed method encodes both quality attributes and semantic content of each video frame
Mirko Agarla +2 more
doaj +3 more sources
Deep attributes and decisions fusion for no-reference video quality analysis [PDF]
Big Data and Computing Visions, 2023 Video Quality Assessment (VQA) is a critical component of various technologies, including automated video broadcasting through displaying technologies.
Adil Baig
doaj +1 more source