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Proceedings Paper

Image interpolation using multiscale geometric representations
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Paper Abstract

With the ever increasing computational power of modern day processors, it has become feasible to use more robust and computationally complex algorithms that increase the resolution of images without distorting edges and contours. We present a novel image interpolation algorithm that uses the new contourlet transform to improve the regularity of object boundaries in the generated images. By using a simple wavelet-based linear interpolation scheme as our initial estimate, we use an iterative projection process based on two constraints to drive our solution towards an improved high-resolution image. Our experimental results show that our new algorithm significantly outperforms linear interpolation in subjective quality, and in most cases, in terms of PSNR as well.

Paper Details

Date Published: 28 February 2007
PDF: 11 pages
Proc. SPIE 6498, Computational Imaging V, 64980A (28 February 2007); doi: 10.1117/12.714510
Show Author Affiliations
Nickolaus Mueller, Univ. of Illinois at Urbana-Champaign (United States)
Yue Lu, Univ. of Illinois at Urbana-Champaign (United States)
Minh N. Do, Univ. of Illinois at Urbana-Champaign (United States)


Published in SPIE Proceedings Vol. 6498:
Computational Imaging V
Charles A. Bouman; Eric L. Miller; Ilya Pollak, Editor(s)

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