Perceptual quality evaluation for image defocus deblurring

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

19 Scopus Citations
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Author(s)

  • Leida Li
  • Ya Yan
  • Yuming Fang
  • Lu Tang
  • Jiansheng Qian

Detail(s)

Original languageEnglish
Pages (from-to)81-91
Journal / PublicationSignal Processing: Image Communication
Volume48
Online published20 Sep 2016
Publication statusPublished - Oct 2016
Externally publishedYes

Abstract

Blur is one of the most common distortion types in image acquisition. Image deblurring has been widely studied as an effective technique to improve the quality of blurred images. However, little work has been done to the perceptual evaluation of image deblurring algorithms and deblurred images. In this paper, we conduct both subjective and objective studies of image defocus deblurring. A defocus deblurred image database (DDID) is first built using state-of-the-art image defocus deblurring algorithms, and subjective test is carried out to collect the human ratings of the images. Then the performances of the deblurring algorithms are evaluated based on the subjective scores. With the observation that the existing image quality metrics are limited in predicting the quality of defocus deblurred images, a quality enhancement module is proposed based on Gray Level Co-occurrence Matrix (GLCM), which is mainly used to measure the loss of texture naturalness caused by deblurring. Experimental results based on the DDID database demonstrate the effectiveness of the proposed method.

Research Area(s)

  • Defocus deblurring, Gray level co-occurrence matrix, Image quality assessment, No-reference, Texture naturalness

Citation Format(s)

Perceptual quality evaluation for image defocus deblurring. / Li, Leida; Yan, Ya; Fang, Yuming; Wang, Shiqi; Tang, Lu; Qian, Jiansheng.

In: Signal Processing: Image Communication, Vol. 48, 10.2016, p. 81-91.

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