Research On Underwater Image Clarification Method And Key Technology

In the real and complex underwater environment,good environmental perception ability is the key to ensure the performance and intelligence level of underwater robots.Due to the special physical and chemical environment of underwater,underwater images often suffer from color distortion,low contrast and hazing,which seriously affects interpretation.Therefore,it is necessary to clarify the imaging of harsh underwater environments and improve the imaging quality of underwater images.The key and difficult issues faced by the current underwater harsh environment imaging clearing method are as follows: Firstly,how to effectively improve the color distortion of underwater images caused by attenuation of the optical signal.Secondly,how to overcome the non-uniform lighting effects introduced by active illumination and avoid a reduction in the dynamic range and contrast of the image.Thirdly,how to effectively suppress the hazing effect caused by the irregular movement of suspended particles and photons in the water as the water depth increases.To solve these problems and obtain high quality underwater images,this paper focuses on three key aspects of underwater image color compensation,non-uniform light removal and improved visibility of textures and structures,and conducts theoretical and experimental research on underwater harsh environment imaging clearing method.The research mainly includes the following three aspects:Aiming at the problem of inconsistent attenuation of different wavelengths of optical signals in water bodies,resulting in color distortion and low definition of underwater images,combined with the optical properties of underwater imaging and the histogram distribution characteristics of clear images,this paper proposes an underwater attenuation image enhancement method with adaptive color compensation and detail optimization(ACCDO).The method fully considers the attenuation level of each optical channel to guide the color correction based on the attenuation image,and introduces a brightness adjustment method to give the output image a good natural appearance.Gradient-oriented local contrast enhancement and multi-scale edge optimization methods are used to process the color-corrected image separately to obtain two clear images with balanced natural colors,high contrast and good preservation of detail information,and then combine with the multi-scale fusion process Artifact-free image fusion is achieved.The experimental results on the UIEB dataset show that the ACCDO method improves the UIQM and BRISQUE scores by 14.32% and 8.53%,respectively,and has fewer free parameters,which can effectively enhance attenuated image contrast,detail information and balance image color.Aiming at the problems of non-uniform illumination introduced by active lighting and the limitations of traditional underwater optical imaging models that assume uniform illumination,combined with color constancy theory and variational models,an underwater image restoration via variational regularization and non-uniform illumination imaging model(VRNU)is proposed.The method constructs an underwater non-uniform illumination imaging model based on the image color constancy theory,selects the optimal background light to estimate the transmission map by a composite prior method that comprehensively considers the characteristics of the background light,establishes a variational model with multiple regularization constraints to refine the transmission map,and successfully integrate the variational method with the non-uniform illumination model.The qualitative and quantitative experimental results show that the restored images obtained by the VRNU method have better color fidelity and detail retention ability,with a mean UCIQE score of 0.604 and a mean UIQM score of 3.888 on the UIEB dataset.Aiming at the problem that the accuracy of the transmittance estimated based on the color channel is limited by the depth of the underwater scene,combined with the physical model of underwater optical imaging and the theory of image blur,an underwater image dehazing method based on image blur estimation of transmission(IBET)is proposed.The method combines the global information of the attenuation channel with the pixel point information to adaptively correct the color deviation of the image so that the histogram distribution of the three channels is similar;the transmission is estimated based on the image blur to remove the blur effect of the underwater image;the multi-scale fusion process is combined Achieve artifact-free fusion of color-corrected images with sharp images.The qualitative and quantitative experimental results show that the enhanced images obtained by the IBET method have good color perception and sharper details,and the UIQM and UCIQE scores on the RUIE dataset are 18.43% and 7.0% higher,respectively,compared to the optimal values in other methods.