Skip to main content
placeholder image

A Spectral and Spatial Approach of Coarse-to-Fine Blurred Image Region Detection

Journal Article


Abstract


  • Blur exists in many digital images, it can be mainly

    categorized into two classes: defocus blur which is caused by optical

    imaging systems and motion blur which is caused by the

    relative motion between camera and scene objects. In this letter,

    we propose a simple yet effective automatic blurred image region

    detection method. Based on the observation that blur attenuates

    high-frequency components of an image, we present a blur metric

    based on the log averaged spectrum residual to get a coarse blur

    map. Then, a novel iterative updating mechanism is proposed to

    refine the blur map from coarse to fine by exploiting the intrinsic

    relevance of similar neighbor image regions. The proposed iterative

    updating mechanism can partially resolve the problem of differentiating

    an in-focus smooth region and a blurred smooth region.

    In addition, our iterative updating mechanism can be integrated

    into other image blurred region detection algorithms to refine the

    final results. Both quantitative and qualitative experimental results

    demonstrate that our proposed method is more reliable and

    efficient compared to various state-of-the-art methods

UOW Authors


  •   Tang, Chang (external author)
  •   Wu, Jin (external author)
  •   Hou, Yonghong (external author)
  •   Wang, Pichao (external author)
  •   Li, Wanqing

Publication Date


  • 2016

Citation


  • Tang, C., Wu, J., Hou, Y., Wang, P. & Li, W. (2016). A Spectral and Spatial Approach of Coarse-to-Fine Blurred Image Region Detection. IEEE Signal Processing Letters, 23 (11), 1652-1656.

Scopus Eid


  • 2-s2.0-84991832996

Number Of Pages


  • 4

Start Page


  • 1652

End Page


  • 1656

Volume


  • 23

Issue


  • 11

Abstract


  • Blur exists in many digital images, it can be mainly

    categorized into two classes: defocus blur which is caused by optical

    imaging systems and motion blur which is caused by the

    relative motion between camera and scene objects. In this letter,

    we propose a simple yet effective automatic blurred image region

    detection method. Based on the observation that blur attenuates

    high-frequency components of an image, we present a blur metric

    based on the log averaged spectrum residual to get a coarse blur

    map. Then, a novel iterative updating mechanism is proposed to

    refine the blur map from coarse to fine by exploiting the intrinsic

    relevance of similar neighbor image regions. The proposed iterative

    updating mechanism can partially resolve the problem of differentiating

    an in-focus smooth region and a blurred smooth region.

    In addition, our iterative updating mechanism can be integrated

    into other image blurred region detection algorithms to refine the

    final results. Both quantitative and qualitative experimental results

    demonstrate that our proposed method is more reliable and

    efficient compared to various state-of-the-art methods

UOW Authors


  •   Tang, Chang (external author)
  •   Wu, Jin (external author)
  •   Hou, Yonghong (external author)
  •   Wang, Pichao (external author)
  •   Li, Wanqing

Publication Date


  • 2016

Citation


  • Tang, C., Wu, J., Hou, Y., Wang, P. & Li, W. (2016). A Spectral and Spatial Approach of Coarse-to-Fine Blurred Image Region Detection. IEEE Signal Processing Letters, 23 (11), 1652-1656.

Scopus Eid


  • 2-s2.0-84991832996

Number Of Pages


  • 4

Start Page


  • 1652

End Page


  • 1656

Volume


  • 23

Issue


  • 11