A multimodal approach with firefly based CLAHE and multiscale fusion for enhancing underwater images

Abstract

Abstract With the advances in technology, humans tend to explore the world underwater in a more constructive way than before. The appearance of an underwater object varies depending on depth, biological composition, temperature, ocean currents, and other factors. This results in colour distorted images and hazy images with low contrast. To address the aforesaid problems, in proposed approach, initially White balance algorithm is carried out to pre-process original underwater image. Contrast enhanced image is achieved by applying the Contrast Limited Adaptive Histogram Equalization algorithm (CLAHE). In CLAHE, tile size and clip limit are the major parameters that control the enhanced image quality. Hence, to enhance the contrast of images optimally, Firefly algorithm is adopted for CLAHE. Dark Channel Prior algorithm (DCP) is modified with guided filter correction to get the sharpened version of the underwater image. Multiscale fusion strategy was performed to fuse CLAHE enhanced and dehazed images. Finally, the restored image is treated with optimal CLAHE to improve visibility of enhanced underwater image. Experimentation is carried out on different underwater image datasets such as U45 and RUIE and resulted in UIQM = 5.1384, UCIQE = 0.6895 and UIQM = 5.4875, UCIQE = 0.6953 respectively which shows the superiority of proposed approach.

Keywords

• White balance
• CLAHE
• DCP
• Multiscale fusion
• Underwater imaging
• Colour correction