Paper Info
Title
Retinally Reconstructed Images (Rris): Digital Images Having A Resolution Match With The Human Eye
Abstract
Current digital image/video storage, transmission and display technologies use uniformly sampled images. On the other hand, the human retina has a nonuniform sampling density that decreases dramatically as the solid angle from the visual fixation axis increases. Therefore, there is sampling mismatch between the uniformly sampled digital images and the retina. This paper introduces Retinally Reconstructed Images (RRIs), a novel representation of digital images, that enables a resolution match with the human retina. To create an RRI, the size of the input image, the viewing distance and the fixation point should be known. In the RRI coding phase, we compute the 'Retinal Codes', which consist of the retinal sampling locations onto which the input image projects, together with the retinal outputs at these locations. In the decoding phase, we use the backprojection of the Retinal Codes onto the input image grid as B-Spline control coefficients, in order to construct a 3-D B-spline surface with nonuniform resolution properties. An RRI is then created by mapping the B-spline surface onto a uniform grid, using triangulation. Transmitting or storing the 'Retinal Codes' instead of the full resolution images enables up to two orders of magnitude data compression, depending on the resolution of the input image, the size of the input image and the viewing distance. The data reduction capability of Retinal Codes and RRI is promising for digital video storage and transmission applications. However, the computational burden can be substantial in the decoding phase.
Year
DOI
Venue
1998
10.1117/12.320151
HUMAN VISION AND ELECTRONIC IMAGING III
Keywords
Field
DocType
retina, fovea, eccentricity, nonuniform sampling, image reconstruction, compression
Iterative reconstruction,Computer vision,Computer science,Optics,Image processing,Image formation,Digital image,Artificial intelligence,Digital imaging,Data compression,Image resolution,Nonuniform sampling
Conference
Volume
ISSN
Citations 
3299
0277-786X
5
PageRank 
References 
Authors
0.56
0
3
Name
Order
Citations
PageRank
Turker Kuyel114117.11
Wilson S. Geisler233331.08
Joydeep Ghosh37041462.41