Efficient non-uniform deblurring based on generalized additive convolution model

Hong Deng, Dongwei Ren, Dapeng Zhang, Wangmeng Zuo, Hongzhi Zhang, Kuanquan Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)


Image with non-uniform blurring caused by camera shake can be modeled as a linear combination of the homographically transformed versions of the latent sharp image during exposure. Although such a geometrically motivated model can well approximate camera motion poses, deblurring methods in this line usually suffer from the problems of heavy computational demanding or extensive memory cost. In this paper, we develop generalized additive convolution (GAC) model to address these issues. In GAC model, a camera motion trajectory can be decomposed into a set of camera poses, i.e., in-plane translations (slice) or roll rotations (fiber), which can both be formulated as convolution operation. Moreover, we suggest a greedy algorithm to decompose a camera motion trajectory into a more compact set of slices and fibers, and together with the efficient convolution computation via fast Fourier transform (FFT), the proposed GAC models concurrently overcome the difficulties of computational cost and memory burden, leading to efficient GAC-based deblurring methods. Besides, by incorporating group sparsity of the pose weight matrix into slice GAC, the non-uniform deblurring method naturally approaches toward the uniform blind deconvolution. Experimental results show that GAC-based deblurring methods can obtain satisfactory deblurring results compared to both state-of-the-art uniform and non-uniform deblurring methods and are much more efficient than non-uniform deblurring methods.
Original languageEnglish
Article number22
Pages (from-to)1-15
Number of pages15
JournalEurasip Journal on Advances in Signal Processing
Issue number1
Publication statusPublished - 1 Dec 2016
Externally publishedYes


  • Blind deconvolution
  • Camera shake
  • Fast Fourier transform
  • Image deblurring
  • Non-uniform deblurring

ASJC Scopus subject areas

  • Signal Processing
  • Hardware and Architecture
  • Electrical and Electronic Engineering


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