Underwater image enhancement with fuzzy histogram equalization and adaptive color correction
(1) * Suharyanto Suharyanto Mail (Faculty of Computer Science, Dian Nuswantoro University, Indonesia)
(2) Pulung Nurtantio Andono Mail (Faculty of Computer Science, Dian Nuswantoro University, Indonesia)
(3) Ahmad Zainul Fanani Mail (Faculty of Computer Science, Dian Nuswantoro University, Indonesia)
(4) Pujiono Pujiono Mail (Faculty of Computer Science, Dian Nuswantoro University, Indonesia)
*corresponding author

Abstract


Marine exploration continues to increase as new technologies, such as computer vision implemented in underwater vehicles and robots, develop. Identifying underwater objects is challenging due to environmental conditions, including poor lighting and color absorption in the viewed image. Underwater image enhancement has been widely applied to overcome these obstacles. Therefore, this study presents a new workflow for improving the quality of underwater images. A combination of the fuzzy histogram equalization (FHE) and adaptive color correction (ACC) methods is used to increase contrast and restore absorbed colors. This study proposes combining FHE and ACC to improve underwater image quality, using the FHE method with the FHEACC method. The results of the UIQM and ENTROPY metrics obtained the highest values, while UCIQE ranked third. This shows that the image quality improved using the FHEACC combination method is objectively better than that achieved with the HE, AHE, CLAHE, FHE, IBLA, RCP, and UDCP methods, especially in maintaining color balance. This research can introduce a new workflow to improve the quality of underwater images by combining Fuzzy Histogram Equalization and Adaptive Color Correction methods, thereby supporting the optimization of underwater image identification systems in wild environments using computer vision technology.

Keywords


Fuzzy histogram equalization; Color correction; Image processing; Image enhancement; Underwater image; Image quality measure

   

DOI

https://doi.org/10.26555/ijain.v12i1.2174 		      

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