Multiple channel adjustment based on composite backbone network for underwater image enhancement Online publication date: Thu, 14-Dec-2023
by Yuhan Chen; Wende Ke; Lei Kou; Qingfeng Li; Dongxin Lu; Yan Bai; Zhen Wang; Junhe Wan
International Journal of Bio-Inspired Computation (IJBIC), Vol. 22, No. 3, 2023
Abstract: In order to heighten enhancement effects for underwater images under different conditions, multiple channel adjustment based on composite backbone network (MC-CBNet) was proposed that skilfully combine the enhancement effect from RGB colour space as well as HSV and Lab. MC-CBNet consists of a preliminary enhance block, a multi-space adjust block and a confidence map block. Preliminary enhance block and multi-space adjust block adjust the images from RGB, HSV and Lab colour spaces respectively. The confidence map is obtained by the ultimate block to fuse the results of different channels. Besides, preliminary enhance block and confidence map block are formed from composite backbones. Experimental results on underwater image enhancement benchmark (UIEB) indicate that our method gets better grades than existing methods under both reference subset and challenging subset evaluation.
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