Application of Super-Resolution Image Reconstruction to Digital Holography
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Application of Super-resolution Image Reconstruction to Digital Holography Shuqun Zhang Department of Computer Science, College of Staten Island, City University of New York, 2800 Victory Boulevard, Staten Island, NY 10314, USA Received 1 December 2004; Revised 10 April 2005; Accepted 18 April 2005 We describe a new application of super-resolution image reconstruction to digital holography which is a technique for threedimensional information recording and reconstruction. Digital holography has suffered from the low resolution of CCD sensors, which significantly limits the size of objects that can be recorded. The existing solution to this problem is to use optics to bandlimit the object to be recorded, which can cause the loss of details. Here super-resolution image reconstruction is proposed to be applied in enhancing the spatial resolution of digital holograms. By introducing a global camera translation before sampling, a highresolution hologram can be reconstructed from a set of undersampled hologram images. This permits the recording of larger objects and reduces the distance between the object and the hologram. Practical results from real and simulated holograms are presented to demonstrate the feasibility of the proposed technique. Copyright © 2006 Hindawi Publishing Corporation. All rights reserved.
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INTRODUCTION
Due to the physical limitations and cost of imaging sensors, it is difficult to obtain high-resolution images in many applications. The low-resolution images are often degraded by noise, blurring, and aliasing effects. Super-resolution image reconstruction has been demonstrated to be very effective in removing these effects by combining several low-resolution images to yield a single high-resolution image. Numerous algorithms for image resolution enhancement have been published since Tsai and Huang [1] first proposed their frequency-domain super-resolution approach. They differ in the observation model, reconstruction method, algorithm domain, and computational cost [2–10]. Most of the superresolution methods use the observation model where the observed low-resolution images result from warping, blurring, and subsampling operations performed on the highresolution image. They work in the spatial domain using maximum a posteriori (MAP) or project onto convex set (POCS) reconstruction technique, and are usually computationally expensive. A complete and comprehensive overview of super-resolution algorithms can be seen in [11, 12]. On the other hand, super-resolution techniques have been successfully used in many applications including medical imaging, remote sensing, satellite imaging, high-definition television, surveillance systems, forensic science, video frame freezing, and printing. This paper explores a new application of super
resolution image reconstruction in digital holography, and analyzes and evaluates the corresponding super-resolution algorithm in the context of digital holography. To my knowledge, this is the first time super-resolution is applied in enhancing the spatial resolution of digi
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