Back to Search Start Over

Compressive color sensing using random complementary color filter array

Authors :
Takeo Azuma
Satoshi Sato
Wakai Nobuhiko
Makoto Nakashizuka
Takamichi Miyata
Kunio Nobori
Source :
MVA
Publication Year :
2017
Publisher :
IEEE, 2017.

Abstract

We propose a new color imaging system based on a compressive sensing technique. Our system consists of a random complementary color filter array (CFA) for random projection and a color reconstruction method for demosaicing. Our CFA overlaps two complementary color filters and consists of six color filters: cyan (C), yellow (Y), magenta (M), C+Y, C+M, and Y+M. By arranging these six color filters randomly, our imaging system achieves pseudo random projection among red (R) /green (G) / blue (B) colors, which is the key technology of compressive sensing. Because this CFA can retain more color information than RGB CFA, the proposed color reconstruction method reduces artifacts at monochromatic edges and in high-frequency regions, and obtains better image quality. As an additional contribution, we introduce saturation consistency to suppress color artifacts in saturated areas, then achieve to 3.3 dB higher quality images than the conventional method.

Details

Database :
OpenAIRE
Journal :
2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA)
Accession number :
edsair.doi...........9c6814c7090beb03de9b8d5de4aca9ce
Full Text :
https://doi.org/10.23919/mva.2017.7986768