Edge-enhancing bi-histogram equalisation using guided image filter

Junwon Mun, Yuneseok Jang, Yoojun Nam, Jaeseok Kim

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Histogram equalisation (HE) is a simple and effective contrast enhancement method. However, it has certain drawbacks, namely, brightness inconsistency, over-enhancement, and noise amplification. In addition, there is structure information loss while processing HE. To overcome those drawbacks simultaneously, we propose a novel edge enhancing bi-histogram equalisation method using guided image filter. In the proposed algorithm, a new adaptive plateau limit and a new edge-enhancing transformation function are proposed. The adaptive plateau limit makes the method robust to various histogram distributions, and the edge-enhancing transformation enhances edges while suppressing noise amplification in the flat region. The performance of the various HE algorithms are evaluated both quantitatively and qualitatively. The qualitative assessment shows that the proposed algorithm avoids over-enhancement and noise amplification, effectively. In addition, the quantitative metrics show that the proposed algorithm outperforms the existing HE algorithms in terms of local contrast, discrete entropy, and perceptual sharpening index.

Original languageEnglish
Pages (from-to)688-700
Number of pages13
JournalJournal of Visual Communication and Image Representation
Volume58
DOIs
Publication statusPublished - 2019 Jan

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All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Media Technology
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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