Gradient-guided color image contrast and saturation enhancement

Haiyan Shi, Ngaiming Kwok, Gu Fang, Stephen Ching-Feng Lin, Ann Lee, Huaizhong Li, Ying-Hao Yu

Research output: Contribution to journalArticlepeer-review

Abstract

Digital color images are capable of presenting hue, saturation, and brightness perceptions. Therefore, quality improvement of color images should be taken into account to enhance all three stimuli. An effective method is proposed that aims at enriching the colorfulness, vividness, and contrast of color images simultaneously. In this method, color correction based on magnitude stretching is carried out first, image enhancement is then derived from an intensity-guided operation that concurrently improves the contrast and saturation qualities. Furthermore, the proposed methodology mitigates the heavy computational burden arising from the need to transform the source color space into an alternative color space in conventional approaches. Experiments had been conducted using a collection of real-world images captured under various environmental conditions. Image quality improvements were observed both from subjective viewing and quantitative evaluation metrics in colorfulness, saturation, and contrast.
Original languageEnglish
Pages (from-to)1-11
Number of pages11
JournalInternational Journal of Advanced Robotic Systems
Volume14
Issue number3
DOIs
Publication statusPublished - 2017

Open Access - Access Right Statement

Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (http://www.creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/ open-access-at-sage).

Keywords

  • brightness perception
  • color
  • environmental conditions

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