An edge-based structural distortion indicator for the quality assessment of 3D synthesized views

International audience3D-TV applications require the generation of novel viewpoints through Depth-Image-Based-Rendering methods. These synthesized views need to be assessed by a reliable quality metric. Most of the proposed metrics are inspired from 2D commonly used quality metrics. Yet, the latter were originally designed to address 2D compression distortions which are different from the distortions related to DIBR processes. We propose an edge-based method that indicates the level of structural degradation in the synthesized image. The first results are encouraging since the correlation to subjective scores is higher than other tested metrics

Objective quality metric for 3D virtual views

In free-viewpoint television (FTV) framework, due to hard-ware and bandwidth constraints, only a limited number of viewpoints are generally captured, coded and transmitted; therefore, a large number of views needs to be synthesized at the receiver to grant a really immersive 3D experience. It is thus evident that the estimation of the quality of the synthesized views is of paramount importance. Moreover, quality assessment of the synthesized view is very challeng-ing since the corresponding original views are generally not available either on the encoder (not captured) or the decoder side (not transmitted). To tackle the mentioned issues, this paper presents an algorithm to estimate the quality of the synthesized images in the absence of the corresponding ref-erence images. The algorithm is based upon the cyclopean eye theory. The statistical characteristics of an estimated cy-clopean image are compared with the synthesized image to measure its quality. The prediction accuracy and reliability of the proposed technique are tested on standard video dataset compressed with HEVC showing excellent correlation results with respect to state-of-the-art full reference image and video quality metrics. Index Terms — Quality assessment, depth image based rendering, view synthesis, FTV, HEVC 1

Quality index for stereoscopic images by jointly evaluating cyclopean amplitude and cyclopean phase

With widespread applications of three-dimensional (3-D) technology, measuring quality of experience for 3-D multimedia content plays an increasingly important role. In this paper, we propose a full reference stereo image quality assessment (SIQA) framework which focuses on the innovation of binocular visual properties and applications of low-level features. On one hand, based on the fact that human visual system understands an image mainly according to its low-level features, local phase and local amplitude extracted from phase congruency measurement are employed as primary features. Considering the less prominent performance of amplitude in IQA, visual saliency is applied into the modification on amplitude. On the other hand, by fully considering binocular rivalry phenomena, we create the cyclopean amplitude map and cyclopean phase map. With this method, both image features and binocular visual properties are mutually combined with each other. Meanwhile, a novel binocular modulation function in spatial domain is also adopted into the overall quality prediction of amplitude and phase. Extensive experiments demonstrate that the proposed framework achieves higher consistency with subjective tests than relevant SIQA metrics

Estimation of signal distortion using effective sampling density for light field-based free viewpoint video

In a light field-based free viewpoint video (LF-based FVV) system, effective sampling density (ESD) is defined as the number of rays per unit area of the scene that has been acquired and is selected in the rendering process for reconstructing an unknown ray. This paper extends the concept of ESD and shows that ESD is a tractable metric that quantifies the joint impact of the imperfections of LF acquisition and rendering. By deriving and analyzing ESD for the commonly used LF acquisition and rendering methods, it is shown that ESD is an effective indicator determined by system parameters and can be used to directly estimate output video distortion without access to the ground truth. This claim is verified by extensive numerical simulations and comparison to PSNR. Furthermore, an empirical relationship between the output distortion (in PSNR) and the calculated ESD is established to allow direct assessment of the overall video distortion without an actual implementation of the system. A small scale subjective user study is also conducted which indicates a correlation of 0.91 between ESD and perceived quality