Open AccessAn Analysis on Pixel Redundancy Structure in Equirectangular Images
Author(s) -
I. Vazquez,
S. Cutchin
Publication year - 2021
Publication title -
computer science research notes
Language(s) - English
Resource type - Conference proceedings
SCImago Journal Rank - 0.11
H-Index - 4
eISSN - 2464-4625
pISSN - 2464-4617
DOI - 10.24132/csrn.2021.3101.6
Subject(s) - computer science , redundancy (engineering) , computer vision , artificial intelligence , jpeg , image quality , pixel , data compression , image compression , visualization , data redundancy , virtual reality , image processing , computer graphics (images) , image (mathematics) , database , operating system
360◦ photogrammetry captures the surrounding light from a central point. To process and transmit these types of images over the network to the end user, the most common approach is to project them onto a 2D image using the equirectangular projection to generate a 360◦ image. However, this projection introduces redundancy into the image, increasing storage and transmission requirements. To address this problem, the standard approach is to use compression algorithms, such as JPEG or PNG, but they do not take full advantage of the visual redundancy produced by the equirectangular projection. In this study of the 360SP dataset (a collection of Google Street View images), we analyze the redundancy in equirectangular images and show how it is structured across the image. Outcomes from our study will support the developing of spherical compression algorithms, improving the immersive experience of Virtual Reality users by reducing loading times and increasing the perceptual image quality.