A reduced-reference perceptual image and video quality metric based on edge preservation
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RESEARCH
Open Access
A reduced-reference perceptual image and video quality metric based on edge preservation Maria G Martini1*, Barbara Villarini2 and Federico Fiorucci2
Abstract In image and video compression and transmission, it is important to rely on an objective image/video quality metric which accurately represents the subjective quality of processed images and video sequences. In some scenarios, it is also important to evaluate the quality of the received video sequence with minimal reference to the transmitted one. For instance, for quality improvement of video transmission through closed-loop optimisation, the video quality measure can be evaluated at the receiver and provided as feedback information to the system controller. The original image/video sequence–prior to compression and transmission–is not usually available at the receiver side, and it is important to rely at the receiver side on an objective video quality metric that does not need reference or needs minimal reference to the original video sequence. The observation that the human eye is very sensitive to edge and contour information of an image underpins the proposal of our reduced reference (RR) quality metric, which compares edge information between the distorted and the original image. Results highlight that the metric correlates well with subjective observations, also in comparison with commonly used full-reference metrics and with a state-of-the-art RR metric. 1 Introduction For recent and emerging multimedia systems and applications, such as modern video broadcasting systems (including DVB/DVB-H, IPTV, webTV, HDTV,...) and telemedical applications, user requirements are going beyond requirements on connectivity, and users now expect the services to meet their requirements on quality. In recent years, the concept of quality of service (QoS) has been augmented towards the new concept of quality of experience (QoE), as the first only focuses on the network performance (e.g., packet loss, delay, and jitter) without a direct link to the perceived quality, whereas the QoE reflects the overall experience of the consumer accessing and using the provided service. The main target in the design of modern multimedia systems is thus the improvement of the (video) quality perceived by the user. For the provision of such quality improvement the availability of an objective quality metric well representing the human perception is crucial. Objective quality assessment methods based on subjective measurements are based either on a perceptual model of the * Correspondence: [email protected] 1 SEC Faculty, School of Computing and Information Systems, Kingston University London, Penrhyn road, Kingston upon Thames KT1 2EE, UK Full list of author information is available at the end of the article
human visual system (HVS) [1], or on a combination of relevant parameters tuned with subjective tests [2,3]. It is also important to evaluate the quality of the received video sequence with minimal reference to the transmitted one [4]. For closed loop opt
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