A multi-objective cotton field image enhancement algorithm based on CHEBWO
In order to enhance the texture clarity of cotton field image ridge features and the contrast between cotton fields and ridge lines,a multi-objective image enhancement algorithm,Chaotic hybrid elite beluga whale optimization(CHEBWO),is proposed,which significantly improves the segmentation accuracy and generalization ability of agricultural machinery visual navigation images.This algorithm is based on Retinex's Auto-MSRCR algorithm and histogram equalization,and a new image weighted fusion model is de-signed.In terms of image evaluation,a new multi-objective weighted evaluation function is designed.The experimental results show that CHEBWO is compared with Retinex based image enhancement algorithms such as SSR,MSR,MSRCR,MSRCP,and histogram equalization based enhancement algorithms such as HE,AHE,and CLAHE.The proposed method has an average improvement of 6.18,42.38,40.41,0.89,and 0.22 in PSNR,AG,SD,IE,SSIM and other indicators.The cotton field image enhancement algo-rithm CHEBWO proposed in this article has outstanding advantages in contrast,clarity,and maintaining ridge texture.
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