Low light image enhancement algorithm based on significance feature detection
Computer vision technology has a wide range of applications in public safety,intelligent transportation,and industrial production,such as crowd analysis,density estimation,and object tracking,recognition,and seg-mentation.However,the actual imaging environment is complex,and due to factors such as rain,fog and low light,the images taken in the outdoor environment often have problems such as color distortion,lack of detail,and poor imaging quality,which seriously affect the subsequent visual tasks.In order to reduce the influence of lighting and rain and fog,improve the imaging quality and improve the visual effect,an image enhancement method based on saliency feature detection is proposed.Firstly,aiming at the problem of image color distortion,a color recovery method based on multi-channel fusion and significance brightness adjustment is proposed.Secondly,in order to enhance the image details,the method based on saliency feature retention is adopted to achieve image detail en-hancement.Experimental results show that the proposed method is superior to the recent algorithm in terms of ob-jective evaluation index and subjective visual effect.