Image Sharpness Assessment by Sparse Representation

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

93 Scopus Citations
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Author(s)

  • Leida Li
  • Dong Wu
  • Jinjian Wu
  • Weisi Lin
  • Alex C. Kot

Detail(s)

Original languageEnglish
Article number7438869
Pages (from-to)1085-1097
Journal / PublicationIEEE Transactions on Multimedia
Volume18
Issue number6
Publication statusPublished - 1 Jun 2016
Externally publishedYes

Abstract

Recent advances in sparse representation show that overcomplete dictionaries learned from natural images can capture high-level features for image analysis. Since atoms in the dictionaries are typically edge patterns and image blur is characterized by the spread of edges, an overcomplete dictionary can be used to measure the extent of blur. Motivated by this, this paper presents a no-reference sparse representation-based image sharpness index. An overcomplete dictionary is first learned using natural images. The blurred image is then represented using the dictionary in a block manner, and block energy is computed using the sparse coefficients. The sharpness score is defined as the variance-normalized energy over a set of selected high-variance blocks, which is achieved by normalizing the total block energy using the sum of block variances. The proposed method is not sensitive to training images, so a universal dictionary can be used to evaluate the sharpness of images. Experiments on six public image quality databases demonstrate the advantages of the proposed method.

Research Area(s)

  • dictionary learning, Image quality assessment, sparse representation

Bibliographic Note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to lbscholars@cityu.edu.hk.

Citation Format(s)

Image Sharpness Assessment by Sparse Representation. / Li, Leida; Wu, Dong; Wu, Jinjian; Li, Haoliang; Lin, Weisi; Kot, Alex C.

In: IEEE Transactions on Multimedia, Vol. 18, No. 6, 7438869, 01.06.2016, p. 1085-1097.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review