Paper Info
Title
Universal sharpening-demosaicing for various types of color-filter array
Abstract
A monochrome-image iterative deblurring method with the classic soft-shrinkage in the shift-invariant Haar wavelet transform domain was recently proposed by R. H. Chan et al. Extending this deblurring method, we present a new iterative sharpening-demosaicing method with the shift-invariant Haar wavelet transform and our color shrinkage utilizing redundant color transform. Our new sharpening-demosaicing method is originally constructed for the Bayer's primary color-filter array (CFA), but its minor modification renders it applicable to various CFA's other than the Bayer's CFA: the complementary CFA, the random arrangement CFA, and so on. Simulation results demonstrate that our new sharpening-demosaicing method in the shift-invariant Haar wavelet transform domain works much more efficiently than our previously proposed sharpening-demosaicing method with the totalvariation regularization in the spatial image-domain.
Year
Venue
Keywords
2010
Aalborg
haar transforms,image colour analysis,image restoration,image segmentation,optical filters,wavelet transforms,bayer primary color-filter array,cfa,color shrinkage,monochrome-image iterative deblurring method,redundant color transform,shift-invariant haar wavelet transform domain,soft-shrinkage,spatial image-domain,total variation regularization,universal sharpening-demosaicing method,iterative methods,color
Field
DocType
ISSN
Computer vision,Pattern recognition,Second-generation wavelet transform,Demosaicing,Artificial intelligence,Discrete wavelet transform,Haar wavelet,Color filter array,Stationary wavelet transform,Wavelet packet decomposition,Mathematics,Wavelet
Conference
2219-5491
Citations 
PageRank 
References 
0
0.34
6
Authors
2
Name
Order
Citations
PageRank
Takashi Komatsu111333.96
Takahiro Saito210030.46