MULTISPECTRAL SNAPSHOT DEMOSAICING VIA NON-CONVEX MATRIX COMPLETION

Author: 

Antonucci, G
Vary, S
Humphreys, D
Lamb, R
Piper, J
Tanner, J
IEEE

Publication Date: 

2019

Journal: 

2019 IEEE DATA SCIENCE WORKSHOP (DSW)

Last Updated: 

2019-09-25T09:05:55.607+01:00

DOI: 

10.1109/DSW.2019.8755561

page: 

227-231

abstract: 

© 2019 IEEE. Snapshot mosaic multispectral imagery acquires an under-sampled data cube by acquiring a single spectral measurement per spatial pixel. Sensors which acquire p frequencies, therefore, suffer from severe 1/p undersampling of the full data cube. We show that the missing entries can be accurately imputed using non-convex techniques from sparse approximation and matrix completion initialised with traditional demosaicing algorithms. In particular, we observe the peak signal-to-noise ratio can typically be improved by 2 dB to 5 dB over current state-of-the-art methods when simulating a p = 16 mosaic sensor measuring both high and low altitude urban and rural scenes as well as ground-based scenes.

Symplectic id: 

992111

Download URL: 

Submitted to ORA: 

Submitted

Publication Type: 

Conference Paper

ISBN-13: 

9781728107080