Scene-based nonuniformity correction using sparse prior

Xingang Mou; Guilin Zhang; Ruolan Hu; Xiao Zhou

doi:10.1117/12.901794

8 December 2011 Scene-based nonuniformity correction using sparse prior

Xingang Mou, Guilin Zhang, Ruolan Hu, Xiao Zhou

Proceedings Volume 8002, MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis; 800214 (2011) https://doi.org/10.1117/12.901794
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China

Abstract

The performance of infrared focal plane array (IRFPA) is known to be affected by the presence of spatial fixed pattern noise (FPN) that is superimposed on the true image. Scene-based nonuniformity correction (NUC) algorithms are widely concerned since they only need the readout infrared data captured by the imaging system during its normal operation. A novel adaptive NUC algorithm is proposed using the sparse prior that when derivative filters are applied to infrared images, the filter outputs tends to be sparse. A change detection module based on results of derivative filters is introduced to avoid stationary object being learned into the background, so the ghosting artifact is eliminated effectively. The performance of the new algorithm is evaluated with both real and simulated imagery.

Citation Download Citation

Xingang Mou, Guilin Zhang, Ruolan Hu, and Xiao Zhou "Scene-based nonuniformity correction using sparse prior", Proc. SPIE 8002, MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis, 800214 (8 December 2011); https://doi.org/10.1117/12.901794

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