Electronic Science and Technology ›› 2019, Vol. 32 ›› Issue (2): 4-8.doi: 10.16180/j.cnki.issn1007-7820.2019.02.002

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Blur Kernel Estimation Algorithm Based on Cepstrum and Spectrum Analysis

WANG Wenkai   

  1. School of Electronic Information Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016, China
  • Received:2018-01-17 Online:2019-02-15 Published:2019-01-02
  • Supported by:
    National Natural Foundation of China(61401198)


Blind image deblurring is a classical image and signal processing problem, which aims to recover a blur kernel and a clear latent image from a blurry image. In the case of fuzzy kernel estimation, the size of blur kernel in earlier algorithms is an input parameter. In recent years, some algorithms can accurately estimate parameterized blur kernel. The none-parameterized blur kernel is more usual in the natural environment, while existing algorithms can not accurately deal with none-parameterized blur kernel. In this paper, cepstrum of image gradient was used to estimate the blur kernel and spectrum was used to further estimate the blur kernel with small size. Experiments results demonstrated that the proposed method could be applied to the fuzzy kernel-scale estimation of natural blurred images in most scenes.

Key words: image deblur, deconvolution, blur kernel estimation, cepstrum analysis, spectrum analysis, fourier transform

CLC Number: 

  • TP391