Robust contrast enhancement of noisy low-light images: Denoising-enhancement-completion

Jaemoon Lim, Jin Hwan Kim, Jae Young Sim, Chang-Su Kim

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

15 Citations (Scopus)


A robust contrast enhancement algorithm for noisy low-light images, called the denoising-enhancement-completion (DEC), is proposed in this work. We observe that noise components in low-light images degrade the performance of the contrast enhancement. Therefore, we first reduce noise components in an input image. Then, we compute the reliability weight for each pixel, by measuring the difference between the input image and the denoised image, and categorize each pixel into one of two classes: noise-free or noisy. We perform the selective histogram equalization to enhance the contrast of the noise-free pixels only. Finally, we restore missing values of the noisy pixels using the enhanced noise-free pixel values, by employing a low-rank matrix completion scheme. Experimental results show that the proposed DEC algorithm removes noise and enhances the contrast of low-light images more effectively than conventional algorithms.

Original languageEnglish
Title of host publicationProceedings - International Conference on Image Processing, ICIP
PublisherIEEE Computer Society
Number of pages5
ISBN (Print)9781479983391
Publication statusPublished - 2015 Dec 9
EventIEEE International Conference on Image Processing, ICIP 2015 - Quebec City, Canada
Duration: 2015 Sept 272015 Sept 30


OtherIEEE International Conference on Image Processing, ICIP 2015
CityQuebec City


  • contrast enhancement
  • Low-light image enhancement
  • matrix completion
  • noise reduction

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing


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