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Proceedings Paper

Multi-frame super resolution robust to local and global motion
Author(s): Zhengping Ji; Qiang Zhang; Lilong Shi; Ilia Ovsiannikov
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Paper Abstract

Super resolution (SR) is to produce a higher resolution image from one or a sequence of low resolution images of a scene. It is essential in medical image analysis as a zooming of a specific area of interest is often required. This paper presents a new multi-frame super resolution (SR) method that is robust to both global and local motion. One of major challenges in multi-frame SR is concurrent global and local motion emergent in the sequence of low resolution images. It poses difficulties in aligning the low resolution images, resulting in artifacts or blurred pixels in the computed high resolution image. We solve the problem via a series of new methods. We first align the upscaled images from bicubic interpolation, and analyze the pixel distribution for the presence of local motion. If local motion is identified, we conduct the local image registration using dense SIFT features. Based on the local registration of images, we analyze pixel locations whose cross-frame variation is high and adaptively select subset of frame pixels in those locations. The adaptive selection of frame pixels is based on a clustering analysis of luminance values of pixels aligned at the same position, such that noise and motion biases are excluded. At the end, a median filter is applied for the selected pixels at each pixel location for super resolution image. We conduct experiments for multi-frame SR, where the proposed method delivers favorable results, especially better than state-of-the-art in dealing with concurrent local and global motions across frames.

Paper Details

Date Published: 13 March 2017
PDF: 7 pages
Proc. SPIE 10137, Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging, 101370Y (13 March 2017); doi: 10.1117/12.2256140
Show Author Affiliations
Zhengping Ji, SAMSUNG Semiconductor, Inc. (United States)
Qiang Zhang, SAMSUNG Semiconductor, Inc. (United States)
Lilong Shi, SAMSUNG Semiconductor, Inc. (United States)
Ilia Ovsiannikov, SAMSUNG Semiconductor, Inc. (United States)

Published in SPIE Proceedings Vol. 10137:
Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging
Andrzej Krol; Barjor Gimi, Editor(s)

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