TY - JOUR
T1 - Simultaneously inpainting in image and transformed domains
AU - Cai, Jian Feng
AU - Chan, Raymond H.
AU - Shen, Lixin
AU - Shen, Zuowei
N1 - Funding Information:
Z. Shen’s research was supported in part by Grant R-146-000-060-112 at the National University of Singapore.
Funding Information:
R. H. Chan’s research was supported in part by HKRGC Grant 400505 and CUHK DAG 2060257.
Funding Information:
L. Shen’s research was supported by the US National Science Foundation under grant DMS-0712827.
PY - 2009/6
Y1 - 2009/6
N2 - In this paper, we focus on the restoration of images that have incomplete data in either the image domain or the transformed domain or in both. The transform used can be any orthonormal or tight frame transforms such as orthonormal wavelets, tight framelets, the discrete Fourier transform, the Gabor transform, the discrete cosine transform, and the discrete local cosine transform. We propose an iterative algorithm that can restore the incomplete data in both domains simultaneously. We prove the convergence of the algorithm and derive the optimal properties of its limit. The algorithm generalizes, unifies, and simplifies the inpainting algorithm in image domains given in Cai et al. (Appl Comput Harmon Anal 24:131-149, 2008) and the inpainting algorithms in the transformed domains given in Cai et al. (SIAM J Sci Comput 30(3):1205-1227, 2008), Chan et al. (SIAM J Sci Comput 24:1408-1432, 2003; Appl Comput Harmon Anal 17:91-115, 2004). Finally, applications of the new algorithm to super-resolution image reconstruction with different zooms are presented.
AB - In this paper, we focus on the restoration of images that have incomplete data in either the image domain or the transformed domain or in both. The transform used can be any orthonormal or tight frame transforms such as orthonormal wavelets, tight framelets, the discrete Fourier transform, the Gabor transform, the discrete cosine transform, and the discrete local cosine transform. We propose an iterative algorithm that can restore the incomplete data in both domains simultaneously. We prove the convergence of the algorithm and derive the optimal properties of its limit. The algorithm generalizes, unifies, and simplifies the inpainting algorithm in image domains given in Cai et al. (Appl Comput Harmon Anal 24:131-149, 2008) and the inpainting algorithms in the transformed domains given in Cai et al. (SIAM J Sci Comput 30(3):1205-1227, 2008), Chan et al. (SIAM J Sci Comput 24:1408-1432, 2003; Appl Comput Harmon Anal 17:91-115, 2004). Finally, applications of the new algorithm to super-resolution image reconstruction with different zooms are presented.
UR - http://www.scopus.com/inward/record.url?scp=67349170815&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=67349170815&partnerID=8YFLogxK
U2 - 10.1007/s00211-009-0222-x
DO - 10.1007/s00211-009-0222-x
M3 - Article
AN - SCOPUS:67349170815
SN - 0029-599X
VL - 112
SP - 509
EP - 533
JO - Numerische Mathematik
JF - Numerische Mathematik
IS - 4
ER -