Open AccessAn Analysis on Pixel Redundancy Structure in Equirectangular Images
Author(s) -
Iker Vazquez,
Steve Cutchin
Publication year - 2021
Publication title -
computer science research notes
Language(s) - English
Resource type - Conference proceedings
eISSN - 2464-4625
pISSN - 2464-4617
DOI - 10.24132/csrn.2021.3002.6
Subject(s) - computer science , redundancy (engineering) , computer vision , artificial intelligence , jpeg , projection (relational algebra) , data compression , pixel , data redundancy , image compression , computer graphics (images) , image processing , image (mathematics) , algorithm , database , operating system
360◦photogrammetry captures the surrounding light from a central point. To process and transmit these types ofimages over the network to the end user, the most common approach is to project them onto a 2D image usingthe equirectangular projection to generate a 360◦image. However, this projection introduces redundancy into theimage, increasing storage and transmission requirements. To address this problem, the standard approach is touse compression algorithms, such as JPEG or PNG, but they do not take full advantage of the visual redundancyproduced by the equirectangular projection. In this study of the 360SP dataset (a collection of Google StreetView images), we analyze the redundancy in equirectangular images and show how it is structured across theimage. Outcomes from our study will support the developing of spherical compression algorithms, improvingthe immersive experience of Virtual Reality users by reducing loading times and increasing the perceptual imagequality.