A Hybrid Method for Enhancement of Both Contrast Distorted and Low-Light Images

Ozturk N., ÖZTÜRK S.

International Journal of Pattern Recognition and Artificial Intelligence, cilt.37, sa.8, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 37 Sayı: 8
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1142/s0218001423540125
  • Dergi Adı: International Journal of Pattern Recognition and Artificial Intelligence
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Computer & Applied Sciences, Metadex, Civil Engineering Abstracts
  • Anahtar Kelimeler: adaptive gamma correction, histogram equalization, Image enhancement, image naturalness, low-light images
  • Erciyes Üniversitesi Adresli: Evet

Özet

Many different histogram equalization (HE)-based image enhancement methods have been developed to overcome the problems of low or high image brightness, contrast sensitivity, and difficulty in revealing details of dark areas under low-light environments. In this paper, a novel image enhancement method based on HE and adaptive gamma correction with weight distribution (AGCWD) is proposed for natural and effective image enhancement. In this method, histogram stretching is performed on Red-Green-Blue (RGB) color components of image, and then the color space of RGB image is converted to Hue-Saturation-Intensity (HSI) color space. The histograms of S and I components are divided into sub-histograms according to the exposure threshold. The underexposure regions are enhanced with a new AGCWD. Then, the color space of HSI image is converted to RGB color space. Finally, the HE is applied to the input image with the obtained image histogram map. Thus, the method has not only effectively prevented the over-enhancement of the contrast but also obtained the quality and natural enhanced image. The proposed method is compared with the most known contrast enhancement methods and low-light enhancement methods. Experimental results have supported that the proposed method outperforms other methods in terms of both visual perception and objective evaluation.