Improving the verification process of video quality metrics

Keimel, Christian; Oelbaum, Tobias; Diepold, Klaus

doi:10.1109/qomex.2009.5246966

Cited by 14 publications

(8 citation statements)

References 26 publications

(29 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This will require coordinated research efforts in the areas of human vision, color science, and video processing and focused research on quality evaluation of recent image and video codecs, such as H.264. In addition, a more sequenced verification process should be followed as specified in [96] to show meaningful results and to have a common basis for the comparison of various techniques.…”

Section: Discussionmentioning

confidence: 99%

Objective Video Quality Assessment Methods: A Classification, Review, and Performance Comparison

Chikkerur

Sundaram

Reisslein

et al. 2011

IEEE Trans. on Broadcast.

540

272

View full text Add to dashboard Cite

Abstract-With the increasing demand for video-based applications, the reliable prediction of video quality has increased in importance. Numerous video quality assessment methods and metrics have been proposed over the past years with varying computational complexity and accuracy. In this paper, we introduce a classification scheme for full-reference and reduced-reference media-layer objective video quality assessment methods. Our classification scheme first classifies a method according to whether natural visual characteristics or perceptual (human visual system) characteristics are considered. We further subclassify natural visual characteristics methods into methods based on natural visual statistics or natural visual features. We subclassify perceptual characteristics methods into frequency-or pixel-domain methods. According to our classification scheme, we comprehensively review and compare the media-layer objective video quality models for both standard resolution and high definition video. We find that the natural visual statistics based MultiScale-Structural SIMilarity index (MS-SSIM), the natural visual feature based Video Quality Metric (VQM), and the perceptual spatio-temporal frequency-domain based MOtion-based Video Integrity Evaluation (MOVIE) index give the best performance for the LIVE Video Quality Database.Index Terms-Full-reference metric, objective video quality, perceptual video quality, reduced-reference metric.

show abstract

Section: Discussionmentioning

confidence: 99%

Objective Video Quality Assessment Methods: A Classification, Review, and Performance Comparison

Chikkerur

Sundaram

Reisslein

et al. 2011

IEEE Trans. on Broadcast.

540

272

View full text Add to dashboard Cite

show abstract

“…ITU-T J. 144, Annex D or the NTIA metric [366,367], calculates spatial and temporal short-term luminance gradients, representing the contrast, motion and activity, for both reference and distorted video. The overall quality value is achieved by temporal pooling using 10% and 90% percentiles that are representative of the worst transient quality for gains and losses in the video sequence.…”

Section: Discussionmentioning

confidence: 99%

Design of Video Quality Metrics with Multi-Way Data Analysis

Keimel¹

2016

T-Labs Series in Telecommunication Services

Self Cite

View full text Add to dashboard Cite

Video quality metrics determine the visual quality of distorted video sequences by using prediction models based on objectively measurable features and are therefore an alternative to the time-consuming and costly subjective video quality assessment. In the conventional design approach to video quality metrics, however, the temporal nature of video is often considered only inadequately due to the use of temporal pooling in the prediction process. Moreover, this approach also often requires knowledge about the human visual system that is not readily or only partly available. In this thesis, I therefore propose a data driven design methodology using multi-way data analysis for the design of video quality metrics. This data driven design approach not only requires no detailed knowledge of the human visual system, but also allows for a proper consideration of the temporal nature of video by using a three-way prediction model, corresponding to the three-way structure of video. Using two simple example metrics, I demonstrate that this purely data driven approach not only outperforms video quality metrics in the state-of-the-art that are often highly optimised towards specific properties of the human visual system, but also that multi-way data analysis methods outperform the combination of two-way data analysis methods and temporal pooling.iii

show abstract

“…Our novel image database has overall 1140 images in total 1920 × 1440 pixel resolution (for big screen testing). In previous research, the image quality assessment was conducted using objective methods [27], while we wanted in the present study to test acceptance of manipulated images with eye movement measurement and to use a method for a subjective quality assessment [9], which would include observers into the testing. The real research problem that arose was not having access to a significant number of previous research studies to base our work on.…”

Section: Image Databasementioning

confidence: 99%

“…The goal was to use this method to determine the influence of image manipulation in the way the participants observed the image. Therefore, TOBII X120, HP ZR24W LCD screen, a PC, controlled dark room environment [27] and TOBII Studio 3.4.4 software, were used (Fig. 4).…”

Section: Eye Movement Measurementmentioning

confidence: 99%

Eye movement analysis of image quality parameters compared to subjective image quality assessment

Ahtik

Starešinič

2017

Teh. vjesn.

View full text Add to dashboard Cite

Original scientific paper Image quality can be determined by using objective or subjective quality assessment methods. Objective methods are based on mathematical measures, such as PSNR, SSIM or RMSE and subjective testing is generally performed by asking the participants which of the given options they prefer or to give a quality score for the presented options. For each image quality evaluation, an image database is required. We developed a novel image database that consists of 30 images on which we applied some manipulations based on different quality parameters. First we conducted testing with the eye-tracking method: by showing images to test participants and measuring their eye movement, we received accurate information about how each of the image quality parameters affected the communication value of each image. The subjective quality assessment method we then employed involved the development of an application for crowdsourcing-based testing. Participants had to determine which of the images the best were. Finally, a correlation between both methods was determined.Keywords: crowdsourcing; eye movement; eye-tracking; image quality; photography; quality parameters Analiza pokreta očiju u određivanju parametara kvalitete slike u usporedbi sa subjektivnom procjenom kvalitete slike Izvorni znanstveni članak Kvaliteta slike može se odrediti primjenom objektivnih ili subjektivnih metoda za procjenu kvalitete. Objektivne se metode zasnivaju na matematičkim mjerama kao što su PSNR, SSIM ili RMSE dok se subjektivno testiranje općenito provodi ili postavljanjem pitanja sudionicima koju od datih opcija preferiraju ili traženjem da dadu ocjenu kvalitete za predložene opcije. Za procjenu kvalitete svake slike potrebna je baza podataka slike. Mi smo razvili novu bazu podataka koja se sastoji od 30 slika na kojima smo napravili određene manipulacije na temelju različitih parametara kvalitete. Najprije smo proveli testiranje metodom praćenja pogleda: pokazivanjem slika sudionicima ispitivanja i mjerenjem pokreta njihovih očiju dobili smo točne informacije o tome kako je svaki od parametara kvalitete slike utjecao na komunikacijsku vrijednost svake slike. Metoda subjektivne procjene kvalitete koju smo zatim primijenili uključila je razvoj aplikacije za ispitivanje zasnovano na masovnoj podršci. Sudionici su trebali odrediti koja od slika je najbolja. Konačno, određena je korelacija između obadvije metode.

show abstract

Improving the verification process of video quality metrics

Cited by 14 publications

References 26 publications

Objective Video Quality Assessment Methods: A Classification, Review, and Performance Comparison

Objective Video Quality Assessment Methods: A Classification, Review, and Performance Comparison

Design of Video Quality Metrics with Multi-Way Data Analysis

Eye movement analysis of image quality parameters compared to subjective image quality assessment

Contact Info

Product

Resources

About