Underwater image comprehensive enhancement method for target recognition

Abstract

The invention relates to an underwater image comprehensive enhancement method for target recognition, which comprises the following steps of: performing red channel color compensation on an underwaterdegraded image, and eliminating contrast reduction caused by forward scattering of the compensated underwater color image by adopting color cast correction. Meanwhile, in order to meet the application requirements of underwater target detection, gamma correction is carried out on the brightness, saturation and hue of an HSV color space, and the problem of blurring caused by dark overall images and backward scattering is solved by adopting single-channel defogging, so that better image contrast and color saturation are obtained, and meanwhile, the definition of details is effectively improved.The method has the advantages that as proved by subjective and objective experiments on various types of underwater images, compared with the conventional underwater image restoration and enhancementalgorithm, the algorithm provided by the invention can effectively improve the color saturation and definition of the underwater images, is wider in application range, and enables a subsequent targetdetection task to obtain higher accuracy.

Description

technical field [0001] The invention belongs to the technical field of image processing and analysis, in particular to an underwater image comprehensive enhancement method for target recognition. Background technique [0002] Underwater vision is an important scientific research basis in ocean exploration, marine biological survey, and underwater engineering monitoring. When light is transmitted in water, the forward scattering makes the point light source diffuse into a circle of confusion during the imaging process, resulting in a blurred image, while the backscattering reduces the contrast of the image, resulting in foggy blur superimposed on the image. Absorption and scattering are produced not only by the water body itself, but also by dissolved organic matter and small floating particles called "sea snow". The concentrations of plankton, colored dissolved organic matter, and total suspended matter and the target distance are also major factors affecting the quality of...

AI Technical Summary

Problems solved by technology

Therefore, most of the underwater images taken have the following problems at the same time: low overall brightness, low contrast, blur, light spots, color cast and noise of various complex factors

Since the distortion of underwater images is composed of a variety of degraded mixtures, a single noise removal, contrast enhancement algorithm, such as histogram correction, gradient transformation and some adaptive smoothing methods such as: low-pass filter, morphological filter Filters, homomorphic filters, Contourlet transform algorithms and various improved wavelet transforms cannot comprehensively solve the degradation of underwater image quality in all aspects, and the ability to adapt to changes in the underwater environment is poor.

[0004] After retrieval, the patent CN 107886486 A discloses an underwater image enhancement method based on dark channel prior and variational Retinex, and the underwater image enhancement method includes the following steps: the original degraded underwater image in the RGB color space based on each channel The mean and variance of the linear stretch to correct the color deviation; apply the dark channel prior theory to the image after the color deviation correction to remove the haze, remove the influence of backscattering, and improve the image contrast; the processed image from the RGB color The space is converted to the LA b color space, and the variational Retinex model is used for the L component to solve the problem of uneven illumination; the enhanced L component is recombined with the a and b components, and converted back to the RGB color space to obtain the final enhanced image; the invention solves It solves the problems of color degradation, low contrast, blurred details, and uneven illumination in underwater images, and improves the visual quality of underwater degraded images, but the image contrast and color saturation are average, which is not conducive to underwater target recognition.

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