This paper proposes an approach to improve the performance of peak signal-to-noise ratio (PSNR) and structural
similarity (SSIM) for image quality assessment in digital cinema applications. Based on the particularities of quality
assessment in a digital cinema setup, some attributes of the human visual system (HVS) are taken into consideration,
including the fovea acuity angle and contrast sensitivity, combined with viewing conditions in the cinema to select
appropriate image blocks for calculating the perceived quality by PSNR and SSIM. Furthermore, as the HVS is not able
to perceive all the distortions because of selective sensitivities to different contrasts, and masking always exists, we
adopt a modified PSNR by considering the contrast sensitivity function and masking effects. The experimental results
demonstrate that the proposed approach can evidently improve the performance of image quality metrics in digital
cinema applications.
One of the key issues for a successful roll out of digital cinema is in the quality it offers. The most practical and least
expensive way of measuring quality of multimedia content is through the use of objective metrics. In addition to the
widely used objective quality metric peak signal-to-noise ratio (PSNR), recently other metrics such as single scale
structural similarity (SS-SSIM) and multi scale structural similarity (MS-SSIM) have been claimed as good alternatives
for estimation of perceived quality by human subjects. The goal of this paper is to verify by means of subjective tests the
validity of such claims for digital cinema content and environment.
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