Full Reference Video Quality Assessment Metric on Base Human Visual System Consistent with PSNR

Mozhaeva, Anastasia; Streeter, Lee; Vlasuyk, I. V.; Potashnikov, A. M.

doi:10.23919/fruct50888.2021.9347604

Cited by 16 publications

(15 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Various full reference VQA parameters are listed in previous studies. [41][42][43] Following are different VQA metrics evaluated for video transmission over OWC-PON architecture:…”

Section: System Designmentioning

confidence: 99%

“…The full reference VQA 42 considers undistorted image as ground truth reference and compares it with the output image from system under consideration. Various full reference VQA parameters are listed in previous studies 41–43 . Following are different VQA metrics evaluated for video transmission over OWC‐PON architecture: Mean square error (MSE): For a video sequence having F frames, MSE 44 is defined as follows:

e_{italicMSE} = \frac{1}{F} \sum_{n = 1}^{F} \{\frac{1}{italicMN} \sum_{x = 1}^{M} \sum_{y = 1}^{N} {((), \overset{F_{n}}{true} ((), x, y) goodbreak- F_{n} ((), x, y))}^{2}\}

where

\overset{truê}{F_{n}} (x, y)

is the distorted n th frame and

F_{n} (x, y)

is the reference n th frame.…”

Section: System Designmentioning

confidence: 99%

See 1 more Smart Citation

Quality assessment for terrestrial digital video broadcast over optical wireless communication‐passive optical network under moderately turbulent regime with spatial diversity

Gill

Singh

et al. 2022

Int J Communication

View full text Add to dashboard Cite

Summary The preceding decade has seen successful rollout of 5G and convergence of broadcast broadband and telecom sector. The near future bandwidth demands for services such as advanced immersive multimedia are even more challenging. This has led to advent of 6G. The access technologies need to provide virtually unlimited data rates to support majority of applications in 6G. The optical wireless communication (OWC) with its inherent advantages is a potential enabler in this scenario. However, phenomenon such as atmospheric turbulence poses a serious degradation to performance of such systems. For multimedia services, end user perception is the ultimate quality indicator. To ascertain this quality in quantitative terms, full reference quality metrics are employed for communication purposes. In this paper, digital video broadcasting terrestrial (DVB‐T) videos with varying complexities are transmitted over OWC‐passive optical network (PON) architecture. For performance enhancement 2 × 2 repetitive coding MIMO is employed with maximal ratio combining receiver. A total of 6 video quality assessment (VQA) metrics are evaluated for the system w.r.t channel parameter as Rytov variance. For all the VQA metrics, an enhancement in the performance is observed by using MIMO technique. This performance improvement is more prominent for more complex video as compared to less complex video. As for the limiting case BER of 10−3 gives a limiting link distance of 1350 m; however with VQA metrics, the limiting case distance is 1280 m. By the use of 2 × 2 MIMO techniques, this distance enhances by 20–25 m.

show abstract

“…Various full reference VQA parameters are listed in previous studies. [41][42][43] Following are different VQA metrics evaluated for video transmission over OWC-PON architecture:…”

Section: System Designmentioning

confidence: 99%

e_{italicMSE} = \frac{1}{F} \sum_{n = 1}^{F} \{\frac{1}{italicMN} \sum_{x = 1}^{M} \sum_{y = 1}^{N} {((), \overset{F_{n}}{true} ((), x, y) goodbreak- F_{n} ((), x, y))}^{2}\}

where

\overset{truê}{F_{n}} (x, y)

is the distorted n th frame and

F_{n} (x, y)

is the reference n th frame.…”

Section: System Designmentioning

confidence: 99%

Quality assessment for terrestrial digital video broadcast over optical wireless communication‐passive optical network under moderately turbulent regime with spatial diversity

Gill

Singh

et al. 2022

Int J Communication

View full text Add to dashboard Cite

show abstract

“…Alongside compression and data transmission, accurate quality estimation is key to maximising use of bandwidth while also maximising the user experience. Video quality methods can be divided into two categories: subjective and objective quality assessment criteria [1]. The human user is typically the final recipient in typical video processing applications, so subjective quality criteria that reflects human visual perception is arguably the more important method of assessing video quality [2].…”

Section: Introductionmentioning

confidence: 99%

“…Unfortunately, popular objective prediction models correlate poorly with subjective perceptions of quality by the human visual system (HVS) and depend on the systems or processes involved [2]. On the other hand, there are algorithmically complex video quality metrics (VQM) based on models of the human visual system [1], [3] , and an open question is whether complex video quality metrics based on models of the human visual system provide significantly better predictions than objective metrics. Another problem when used of visual models, is in developing video quality metrics we must represent the HVS in software, a task impeded by the limited new fundamental knowledge of the HVS perception of video content using modern equipment.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Video Quality Assessment Considering the Features of the Human Visual System

Mozhaeva

Mazin

Cree

et al. 2023

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

Nowadays, numerous video compression quality assessment metrics are available. Some of these metrics are "objective" and only tangentially represent how a human observer rates video quality. On the other hand, models of the human visual system have been shown to be effective at describing spatial coding. In this work we propose a new quality metric which extends the peak signal to noise ratio metric with features of the human visual system measured using modern LCD screens. We also analyse the current visibility models of the early visual system and compare the commonly used quality metrics with metrics containing data modelling human perception. We examine the Pearson's linear correlation coefficient of the various video compression quality metrics with human subjective scores on videos from the publicly available Netflix data set. Of the metrics tested, our new proposed metric is found to have the most stable high performance in predicting subjective video compression quality.

show abstract

Achieving Procedure-Aware Instructional Video Correlation Learning Under Weak Supervision from a Collaborative Perspective

He,

Liu,

et al. 2024

Int J Comput Vis

View full text Add to dashboard Cite

Full Reference Video Quality Assessment Metric on Base Human Visual System Consistent with PSNR

Cited by 16 publications

References 9 publications

Quality assessment for terrestrial digital video broadcast over optical wireless communication‐passive optical network under moderately turbulent regime with spatial diversity

Quality assessment for terrestrial digital video broadcast over optical wireless communication‐passive optical network under moderately turbulent regime with spatial diversity

Video Quality Assessment Considering the Features of the Human Visual System

Achieving Procedure-Aware Instructional Video Correlation Learning Under Weak Supervision from a Collaborative Perspective

Contact Info

Product

Resources

About