Visual contrast enhancement algorithm based on histogram equalization

Chih Chung Ting, Bing-Fei Wu, Meng Liang Chung*, Chung Cheng Chiu, Ya Ching Wu

*Corresponding author for this work

Research output: Contribution to journalArticle

14 Scopus citations

Abstract

Image enhancement techniques primarily improve the contrast of an image to lend it a better appearance. One of the popular enhancement methods is histogram equalization (HE) because of its simplicity and effectiveness. However, it is rarely applied to consumer electronics products because it can cause excessive contrast enhancement and feature loss problems. These problems make the images processed by HE look unnatural and introduce unwanted artifacts in them. In this study, a visual contrast enhancement algorithm (VCEA) based on HE is proposed. VCEA considers the requirements of the human visual perception in order to address the drawbacks of HE. It effectively solves the excessive contrast enhancement problem by adjusting the spaces between two adjacent gray values of the HE histogram. In addition, VCEA reduces the effects of the feature loss problem by using the obtained spaces. Furthermore, VCEA enhances the detailed textures of an image to generate an enhanced image with better visual quality. Experimental results show that images obtained by applying VCEA have higher contrast and are more suited to human visual perception than those processed by HE and other HE-based methods.

Original languageEnglish
Pages (from-to)16981-16999
Number of pages19
JournalSensors (Switzerland)
Volume15
Issue number7
DOIs
StatePublished - 13 Jul 2015

Keywords

  • Contrast enhancement
  • Dynamic range
  • Histogram equalization (HE)
  • Just-noticeable difference (JND)

Fingerprint Dive into the research topics of 'Visual contrast enhancement algorithm based on histogram equalization'. Together they form a unique fingerprint.

  • Cite this