Towards the Perceptual Quality Evaluation of Compressed Light Field Images

Paudyal, Pradip; Battisti, Federica; Sjöström, Mårten; Olsson, Roger; Carli, Marco

doi:10.1109/tbc.2017.2704430

Cited by 66 publications

(29 citation statements)

References 67 publications

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“…Image and video QoE analysis: Rapid growth of social media networks and competition of earning revenues between service providers encourage to provide QoS to end users and consider their experience for future development. Image and video sharing is a common feature of social media networks but high quality images and videos require more storage and management so quality, compression, contents analysis of image, video and audios are further consideration for future work (Tao et al 2015, Paudyal et al 2017.…”

Section: Open Research Issuesmentioning

confidence: 99%

Application of Quality of Experience in Networked Services: Review, Trend & Perspectives

Laghari

Shafiq

et al. 2018

Syst Pract Action Res

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Over the last decade, there has been an exponential growth of services over the Internet. Services such as online gaming are gaining popularity, whereas, Voice over Internet (VoIP) has been well established. Storage, management and processing of data have moved away from the devices to the cloud. Quality of experience (QoE) defined as the user's perception of service quality is utilized in different technologies, services and products for improving end user satisfaction and provides quality of service (QoS) according to their demands. In this paper, we describe the utilization of QoE in different technologies, services and products for improving end user satisfaction. Specifically, we present the latest developments in QoE in multimedia services, network management, VoIP, web development, games and cloud computing. Finally, we discuss the current research, solutions and present open issues of future research in QoE.

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Section: Open Research Issuesmentioning

confidence: 99%

Application of Quality of Experience in Networked Services: Review, Trend & Perspectives

Laghari

Shafiq

et al. 2018

Syst Pract Action Res

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“…We conducted experiments on four publicly available datasets, namely Win5-LID [51], MPI-LFA [52], SMART [53] and VALID [54] to examine our proposed NR-LFQA model.…”

Section: Datasetsmentioning

confidence: 99%

No-Reference Light Field Image Quality Assessment Based on Spatial-Angular Measurement

Shi

Zhou

Chen

et al. 2020

IEEE Trans. Circuits Syst. Video Technol.

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Light field image quality assessment (LFI-QA) is a significant and challenging research problem. It helps to better guide light field acquisition, processing and applications. However, only a few objective models have been proposed and none of them completely consider intrinsic factors affecting the LFI quality. In this paper, we propose a No-Reference Light Field image Quality Assessment (NR-LFQA) scheme, where the main idea is to quantify the LFI quality degradation through evaluating the spatial quality and angular consistency. We first measure the spatial quality deterioration by capturing the naturalness distribution of the light field cyclopean image array, which is formed when human observes the LFI. Then, as a transformed representation of LFI, the Epipolar Plane Image (EPI) contains the slopes of lines and involves the angular information. Therefore, EPI is utilized to extract the global and local features from LFI to measure angular consistency degradation. Specifically, the distribution of gradient direction map of EPI is proposed to measure the global angular consistency distortion in the LFI. We further propose the weighted local binary pattern to capture the characteristics of local angular consistency degradation. Extensive experimental results on four publicly available LFI quality datasets demonstrate that the proposed method outperforms state-of-the-art 2D, 3D, multi-view, and LFI quality assessment algorithms.Index Terms-Light field image, quality assessment, epipolar plane image, naturalness, spatial quality, angular consistency.

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“…The immense data requirements need to be kept at bay, while preserving a desired level of perceived quality. The works of Viola et al [43] [44] and Paudyal et al [45] address this topic, from the angle of both objective and subjective quality assessment.…”

Section: Perceived Quality Of Light Field Visualizationmentioning

confidence: 99%

Evaluation of the Concept of Dynamic Adaptive Streaming of Light Field Video

Kara

Cserkaszky

Martini

et al. 2018

IEEE Trans. on Broadcast.

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Abstract-Light field visualization has progressed and developed significantly in the past years. At the time of this paper, light field displays are utilized in the industry and they are commercially available as well. Although their appearance on the consumer market is approaching, many potential applications of light field technology have not yet been addressed, such as video streaming. In this paper, we present our research on the dynamic adaptive streaming of light field video. In order to evaluate the presented concept of quality switching, we carried out a series of subjective tests, where test participants were shown light field videos containing stallings and switches in spatial and angular resolution.

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Towards the Perceptual Quality Evaluation of Compressed Light Field Images

Cited by 66 publications

References 67 publications

Application of Quality of Experience in Networked Services: Review, Trend & Perspectives

Application of Quality of Experience in Networked Services: Review, Trend & Perspectives

No-Reference Light Field Image Quality Assessment Based on Spatial-Angular Measurement

Evaluation of the Concept of Dynamic Adaptive Streaming of Light Field Video

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