21 May 2018 HMD quality evaluation of projected image: hardware assessment and software evaluation for distortions correction
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Abstract
Studies on Head Mounted Displays (HMDs) to integrate increased sensory capacities to the wearer are growing fast over the years for applications in Augmented (AR), Virtual (VR) and Mixed Reality (MR). In this work, we focus our attention on the characterisation of the projected image from the Optical Module (OM) equipped on board of “F4” model (AR mask for industrial users) produced by GlassUp. We have used our own system to test the quality assessment process, but it can be applied also to other kinds of OM. The major difference between real eye and the emulated one is that in the first one the projected image is elaborated as a continuum by our brain while in the second one the acquiring detector is discretised in pixels. After a proper resize, the images acquired by the detector (1900x1200 px) can be analysed with respect to the original images used as input for the display in the OM (640x480 px). Based on the Structural Similarity (SSIM) theory, we propose the definition of a new index (F-SSIM) to extract more reliable information on the quality of projected images. This approach can be used both for hardware validation trial and evaluation of digital corrections for the pincushion and vignetting optical distortions. The quality assessments proposed in this work define an innovative resize approach of the reference and acquired images for an optimal structural similarity comparison. The results for F-SSIM and SSIM analysis are compared and discussed.
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Thomas Miletti, Nicola Truant, Entela Gurabardhi, Enzo Francesca, Francesco Giartosio, Marco Francardi, "HMD quality evaluation of projected image: hardware assessment and software evaluation for distortions correction", Proc. SPIE 10676, Digital Optics for Immersive Displays, 106760C (21 May 2018); doi: 10.1117/12.2306270; https://doi.org/10.1117/12.2306270
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