Spatially-Varying Sharpness Map Estimation Based on the Quotient of Spectral Bands

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Natural images suffer from defocus blur due to the presence of objects at different depths from the camera. Automatic estimation of spatially-varying sharpness has several applications including depth estimation, image quality assessment, information retrieval, image restoration among others. In this paper, we propose a sharpness metric based on the quotient of high- to low-frequency bands of the log-spectrum of the image gradients. Using the proposed sharpness metric, we obtain a descriptive dense sharpness map. We also propose a simple yet effective method to segment out-of-focus regions using a global threshold which is defined using weak textured regions present in the input image. Results over two publicly available databases show that the proposed method provides competitive performance when compared with state-of-the-art methods.

Original languageEnglish (US)
Title of host publication2019 IEEE International Conference on Image Processing, ICIP 2019 - Proceedings
PublisherIEEE Computer Society
Pages4020-4024
Number of pages5
ISBN (Electronic)9781538662496
DOIs
StatePublished - Sep 2019
Event26th IEEE International Conference on Image Processing, ICIP 2019 - Taipei, Taiwan, Province of China
Duration: Sep 22 2019Sep 25 2019

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2019-September
ISSN (Print)1522-4880

Conference

Conference26th IEEE International Conference on Image Processing, ICIP 2019
CountryTaiwan, Province of China
CityTaipei
Period9/22/199/25/19

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Keywords

  • blur detection
  • Defocus
  • out-of-focus
  • spatially varying

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

Cite this

Andrade, J., Turaga, P., & Spanias, A. (2019). Spatially-Varying Sharpness Map Estimation Based on the Quotient of Spectral Bands. In 2019 IEEE International Conference on Image Processing, ICIP 2019 - Proceedings (pp. 4020-4024). [8803406] (Proceedings - International Conference on Image Processing, ICIP; Vol. 2019-September). IEEE Computer Society. https://doi.org/10.1109/ICIP.2019.8803406