Title
Optimized Multi-Spectral Filter Array Based Imaging of Natural Scenes.
Abstract
Multi-spectral imaging using a camera with more than three channels is an efficient method to acquire and reconstruct spectral data and is used extensively in tasks like object recognition, relighted rendering, and color constancy. Recently developed methods are used to only guide content-dependent filter selection where the set of spectral reflectances to be recovered are known a priori. We present the first content-independent spectral imaging pipeline that allows optimal selection of multiple channels. We also present algorithms for optimal placement of the channels in the color filter array yielding an efficient demosaicing order resulting in accurate spectral recovery of natural reflectance functions. These reflectance functions have the property that their power spectrum statistically exhibits a power-law behavior. Using this property, we propose power-law based error descriptors that are minimized to optimize the imaging pipeline. We extensively verify our models and optimizations using large sets of commercially available wide-band filters to demonstrate the greater accuracy and efficiency of our multi-spectral imaging pipeline over existing methods.
Year
DOI
Venue
2018
10.3390/s18041172
SENSORS
Keywords
Field
DocType
multi-spectral imaging,content independent channel selection,multispectral filter array,demosaicing
Color constancy,Computer vision,Spectral imaging,A priori and a posteriori,Electronic engineering,Demosaicing,Spectral density,Artificial intelligence,Engineering,Color filter array,Rendering (computer graphics),Cognitive neuroscience of visual object recognition
Journal
Volume
Issue
Citations 
18
4.0
0
PageRank 
References 
Authors
0.34
16
4
Name
Order
Citations
PageRank
Yuqi Li1267.16
Aditi Majumder278862.12
Hao Zhang320364.03
M. Gopi427224.83