IEIE Transactions on Smart Processing and Computing

대한전자공학회 (The Institute of Electronics and Information Engineers)
권호 표지

The Vaguelette-Curvelet Decomposition for Image Deblurring

  • Cho, Changhun (Image Processing and Intelligent Systems Laboratory, Graduate School of Advanced Imaging Science, Multimedia, and Film Seoul, Chung-Ang University) ;
  • Katsaggelos, Aggelos K. (Department of Electrical Engineering and Computer Science, Northwestern University) ;
  • Paik, Joonki (Image Processing and Intelligent Systems Laboratory, Graduate School of Advanced Imaging Science, Multimedia, and Film Seoul, Chung-Ang University)
  • 투고 : 2012.07.14
  • 심사 : 2012.08.20
  • 발행 : 2013.06.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

We present a vaguelette-curvelet decomposition based image deblurring algorithm. We first perform denoising based on the hard-thresholding rule by estimating unknown curvelet coefficients. The proposed algorithm then calculates vaguelette functions by deconvolving the curvelet bases by the point spread function. Vaguelette transform is finally performed to make a clearly restored image. Since the proposed algorithm uses the curvelet transform to sensitively express the edges in all directions, it is possible to restore images with more naturally preserved edges in all directions.

키워드