Title :
Multi-capture High Dynamic Range compressive imaging
Author :
Guicquero, W. ; Dupret, A. ; Vandergheynst, P.
Author_Institution :
CEA-Leti, Grenoble, France
Abstract :
We propose a novel approach to reconstruct High Dynamic Range images from few compressive measurements. The reconstruction algorithm directly merges the information of multi-capture bayerized images. It simultaneously performs demosaicing and naive predefined tone-mapping. Two different color spaces are taken into account at the reconstruction stage to add multiple constraints on the signal. The proposed method provides a new way to compensate nonlinearities due to saturation issues in the case of multi-capture. This technique requires some prior knowledge of the pixel behavior at the sensor level. Yet, it could already be applied using existing compressive measurements performed by actual Compressive Sensing image sensors such as [1]. Future compressive sensing imagers would be able to efficiently acquire multi-capture high dynamic range compressed images.
Keywords :
compressed sensing; image colour analysis; image reconstruction; image segmentation; image sensors; color spaces; compressive measurements; compressive sensing image sensors; image demosaicing; image reconstruction; multicapture bayerized image; multicapture high dynamic range compressive imaging; naive predefined tone-mapping; nonlinearities compensation; pixel behavior; reconstruction stage; Compressed sensing; Dynamic range; Equations; Image coding; Image color analysis; Image reconstruction; Mathematical model; Compressive Sensing; Demosacing; High Dynamic Range Imaging; Redundant Wavelet Dictionary; Total Variation;
Conference_Titel :
Signals, Systems and Computers, 2013 Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
978-1-4799-2388-5
DOI :
10.1109/ACSSC.2013.6810247