Underwater image enhancement using contrast limited adaptive histogram equalization and layered difference representation


MULTIMEDIA TOOLS AND APPLICATIONS, vol.80, no.10, pp.15067-15091, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 80 Issue: 10
  • Publication Date: 2021
  • Doi Number: 10.1007/s11042-020-10426-2
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, FRANCIS, ABI/INFORM, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC, zbMATH
  • Page Numbers: pp.15067-15091
  • Keywords: CLAHE, LDR, Contrast correction, Color correction, COLOR CORRECTION
  • Karadeniz Technical University Affiliated: Yes


Underwater images, which have low contrast and visibility as a result of selective attenuation based on the wavelength of the light passing through water, needs some corrections to extract meaningful information from them. In this paper, we aim to combine two different approaches; global and local contrast enhancement techniques, to obtain better visual quality while enhancing image contrasts on underwater images. While global technique (LDR) ensures the overall enhancement of the image, local technique (CLAHE) considers local brightness features of the image in RGB color space. The proposed method also applies local color correction on underwater image. While methods in the literature apply various approaches on the global histogram of channels, our method divides underwater image into non-overlapping sub-blocks and apply histogram equalization on them. The method uses HSV color space and especially S, V components for color correction. The results of the qualitative analysis show that it produces very good images, in contrast, color, and detail compared to other enhancement methods. The proposed method also decreases the effect of under- and over-enhanced areas and the blue-green effect on the output image. However, the visibility of the objects in the images are increased by color correction. For quantitative analysis, the proposed method produces the highest average value of entropy (7.83), EMEE (32.06), EME (40.97), average gradient (152.55), and Sobel count (130393) for 200 underwater images.