Light field rendering promises to overcome the limitations of stereoscopic representation by allowing for a more seamless transition between multiple point of views, thus giving a more faithful representation of 3D scenes. However, it is indisputable that there is a need for light field displays on which the data can be natively visualised, fuelled by the recent innovations in the realm of acquisition and compression of light field contents. Assessing the visual quality of light field contents on native light field display is of extreme importance in future development of both new rendering methods, as well as new compression solutions. However, the limited availability of light field displays restrict the possibility of using them to carry out subjective tests. Moreover, hardware limitations in prototype models may lessen considerably the perceptual quality of experience in consuming light field contents. In this paper, we compare three different compression approaches for multi-layer displays, through both objective quality metrics and subjective quality assessment. Furthermore, we analyze the results obtained through subjective tests conducted using a prototype multi-layer display, and a recently-proposed framework to conduct quality assessment of light field contents rendered through a tensor display simulator in 2D screens. Using statistical tools, we assess the correlation among the two settings and we draw useful conclusions for future design of compression solutions and subjective tests for light field contents with muti-layer rendering.
The JPEG committee (Joint Photographic Experts Group, formally known as ISO/IEC SC29 WG1) is currently in the process of standardizing JPEG XS, a new interoperable solution for low-latency, lightweight and visually lossless compression of image and video. This codec is intended to be used in applications where content would usually be transmitted or stored in uncompressed form such as in live production, display links, virtual and augmented reality, self driving vehicles or frame buffers. It achieves bandwidth and power reduction for transparent and low latency coding for compression ratios ranging from 2:1 to 6:1. The subjective assessment of the impact of visually lossless compression poses particular challenges. This paper describes the subjective quality evaluation conducted on the JPEG XS core coding system. In particular, it details the test procedures and compares the results obtained by the different evaluation laboratories involved in the standardization effort.
In recent years, light field imaging has attracted the attention of the academic and industrial communities thanks to its enhanced rendering capabilities that allow to visualise contents in a more immersive and interactive way. However, those enhanced capabilities come at the cost of a considerable increase in content size when compared to traditional image and video applications. Thus, advanced compression schemes are needed to efficiently reduce the volume of data for storage and delivery of light field content. In this paper, we introduce a novel method for compression of light field images. The proposed solution is based on a graph learning approach to estimate the disparity among the views composing the light field. The graph is then used to reconstruct the entire light field from an arbitrary subset of encoded views. Experimental results show that our method is a promising alternative to current compression algorithms for light field images, with notable gains across all bitrates with respect to the state of the art.
In recent years, light field has experienced a surge of popularity, mainly due to the recent advances in acquisition and rendering technologies that have made it more accessible to the public. Thanks to image-based rendering techniques, light field contents can be rendered in real time on common 2D screens, allowing virtual navigation through the captured scenes in an interactive fashion. However, this richer representation of the scene poses the problem of reliable quality assessments for light field contents. In particular, while subjective methodologies that enable interaction have already been proposed, no work has been done on assessing how users interact with light field contents. In this paper, we propose a new framework to subjectively assess the quality of light field contents in an interactive manner and simultaneously track users behaviour. The framework is successfully used to perform subjective assessment of two coding solutions. Moreover, statistical analysis performed on the results shows interesting correlation between subjective scores and average interaction time.
Plenoptic content is becoming increasingly popular thanks to the availability of acquisition and display devices. Thanks to image-based rendering techniques, a plenoptic content can be rendered in real time in an interactive manner allowing virtual navigation through the captured scenes. This way of content consumption enables new experiences, and therefore introduces several challenges in terms of plenoptic data processing, transmission and consequently visual quality evaluation. In this paper, we propose a new methodology to subjectively assess the visual quality of plenoptic content. We also introduce a prototype software to perform subjective quality assessment according to the proposed methodology. The proposed methodology is further applied to assess the visual quality of a light field compression algorithm. Results show that this methodology can be successfully used to assess the visual quality of plenoptic content.