Multispectral snapshot demosaicing via non-convex matrix completion

Autor:	Antonucci, Giancarlo A., Vary, Simon, Humphreys, David, Lamb, Robert A., Piper, Jonathan, Tanner, Jared
Rok vydání:	2019
Předmět:	Computer Science - Computer Vision and Pattern Recognition 94A08 15A83 I.4.5 I.4.9
Druh dokumentu:	Working Paper
DOI:	10.1109/DSW.2019.8755561
Popis:	Snapshot mosaic multispectral imagery acquires an undersampled 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 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. Comment: 5 pages, 2 figures, 1 table
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1902.11032 Zobrazit plný text záznamu View this record from Arxiv