Superresolution under Photometric Diversity of Images
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Research Article Superresolution under Photometric Diversity of Images Murat Gevrekci and Bahadir K. Gunturk Department of Electrical Engineering, Louisiana State University, Baton Rouge, LA 70809, USA Received 31 August 2006; Accepted 9 April 2007 Recommended by Richard R. Schultz Superresolution (SR) is a well-known technique to increase the quality of an image using multiple overlapping pictures of a scene. SR requires accurate registration of the images, both geometrically and photometrically. Most of the SR articles in the literature have considered geometric registration only, assuming that images are captured under the same photometric conditions. This is not necessarily true as external illumination conditions and/or camera parameters (such as exposure time, aperture size, and white balancing) may vary for different input images. Therefore, photometric modeling is a necessary task for superresolution. In this paper, we investigate superresolution image reconstruction when there is photometric variation among input images. Copyright © 2007 M. Gevrekci and B. K. Gunturk. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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INTRODUCTION
Detailed visual descriptions are demanded in a variety of commercial and military applications, including surveillance systems, medical imaging, and aerial photography. Imaging devices have limitations in terms of, for example, spatial resolution, dynamic range, and noise characteristics. Researchers are working to improve sensor characteristics by exploring new materials, manufacturing processes, and technologies. In addition to the developments in sensor technology, image processing ideas are also explored to improve image quality. One promising research direction is the application of superresolution image reconstruction, where multiple images are combined to improve spatial resolution. Super resolution (SR) algorithms exploit information diversity among overlapping images through subpixel image registration. Accuracy of subpixel registration allows us to obtain frequency components that are unavailable in individual images. The idea of SR image reconstruction has been investigated extensively, and commercial products are becoming available [1, 2]. For detailed literature surveys on SR, we refer the readers to other sources [3–7]. In this paper, we focus on a new issue in SR: how to perform SR when some of the input images are photometrically different than the others? Other than a few recent papers, almost all SR algorithms in the literature assume that input images are captured under the same photometric conditions. This is not necessarily true in general. External illumina-
tion conditions may not be identical for each image. Images may be captured using different cameras that have different radiometric response curves and settings (such as exposure time and ISO settings). Even if the same camera is used for a
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