In this paper, we propose a high-resolution image reconstruction algorithm considering inaccurate subpixel registration. A regularized iterative reconstruction algorithm is adopted to overcome the ill-posedness problem resulting from inaccurate subplxel registration. In particular, we use multichannel image reconstruction algorithms suitable for applications with multiframe environments. Since the registration error in each low-resolution image has a different pattern, the regularization parameters are determined adaptively for each channel. We propose two methods for estimating the regularization parameter automatically. The proposed algorithms are robust against the registration error noise, and they do not require any prior information about the original image or the registration error process. Information needed to determine the regularization parameter and to reconstruct the image is updated at each iteration step based on the available partially reconstructed image. Experimental results indicate that the proposed algorithms outperform conventional approaches in terms of both objective measurements and visual evaluation.
Bibliographical noteFunding Information:
Manuscript received February 4, 2002; revised December 17, 2002. This work was supported in part by Korea Science and Engineering Foundation through Biometrics Engineering Research Center at Yonsei Univerisity. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Tamas Sziranyi.
All Science Journal Classification (ASJC) codes
- Computer Graphics and Computer-Aided Design