Research on multi-constrained priori image enhancement for deep-sea human occupied vehicle
A Bayesian Retinex image enhancement method based on multi-constraint prior was proposed to solve the problem of image degradation caused by artificial light source illumination of deep-sea Human Occupied Vehicle,such as color distortion,scattering blur and uneven illumination.The method first through a statistical color correction method based on the image color correction processing,and then the illumination map successively smoothing,structure and uneven illu-mination highlight region three prior,and the three prior conditions into the Bayesian model,and select the L component in the Lab color space as the initial illumination map to optimize the illumination map estimation.Finally,enhanced deep sea images were obtained by gamma correction for the illumination and reflection maps.The experimental results show that the proposed method has an average running time of 4.39 s,which has low complexity and is more suitable for image enhance-ment work in harsh deep-sea environments,and the processed deep-sea images have better observation effect.
underwater image enhancementBayesian estimationRetinex theorydeep-sea human occupied vehicle
万方数据
维普
