Due to the scattering and absorption of particulate matter in the atmosphere,remote sensing images often suffer from problems such as blurred details and reduced contrast,which seriously affect their visual quality.To address these is-sues,a remote sensing image dehazing method based on the fusion of global and local advantages features is proposed.Specifically,the dark channel prior is employed to haze removal preprocessing on the raw image.Subsequently,a multi-exposure fusion strategy and integration methods such as integral and square integral is utilized to combine dominant fea-ture information from image regions,enhancing global and local contrast.Finally,a pyramid fusion approach is employed to adaptively select salient features to enhance global and local contrast,resulting in a clarified image.The experimental results show that the proposed method outperforms other methods in remote sensing image dehazing,and the processed image exhibits good performance in terms of dark region exposure,global contrast enhancement,and local detail enhance-ment.
维普
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