Adaptive gradient gain underwater image enhancement method based on target imaging model

Abstract

The invention discloses an adaptive gradient gain underwater image enhancement method based on a target imaging model. The method comprises the following steps of performing global background illumination vector estimation; dividing an integral image into a plurality of blocked images with the same dimension; performing optimized transmissivity estimation; obtaining an estimated value of the to-be-improved transmissivity; calculating a dehazing clear image which corresponds with an original observed image; calculating a gradient image which corresponds with the original observed image; obtaining an enhanced image with added gradient information based on an original observation image; and performing quantitative evaluation on the enhanced image. According to the method of the invention, theself information of the image is detected by means of a single inhomogeneous-brightness low-signal-to-noise-ratio low-contrast underwater target; de-noising enhancing processing, adaptive gain and integrated quantitative evaluation index evaluation are performed on the image for obtaining an adaptive gradient gain enhanced image based on a target imaging model. The adaptive gradient gain underwater image enhancement method can sufficiently utilize the abundant gradient information of the image for realizing image enhancement processing, thereby improving visual quality of the processed imageand realizing abundant texture information.

Description

technical field [0001] The invention belongs to the field of image information processing, and in particular relates to an adaptive gradient gain underwater image enhancement method based on a target imaging model. Background technique [0002] Underwater target detection images often have special conditions such as non-uniform brightness, low signal-to-noise ratio, and low contrast, which lead to serious degradation of underwater images. Commonly used underwater target detection image enhancement algorithms are mainly divided into modifying the illumination of underwater images and suppressing There are two categories of image contrast to preserve image edges, but it will inevitably reduce the visual quality of the detected image. Traditional image enhancement algorithms based on contrast enhancement have great limitations. For example, histogram equalization (HE) enhances the image globally, but increases noise or introduces new noise. Contrast limited adaptive histogram ...

AI Technical Summary

Problems solved by technology

However, the existing prior knowledge has its own limitations, especially when the target brightness is higher than the background brightness, it is often difficult to obtain the expected effect

Due to the influence of the optical properties of water and various particles, plankton and water flow in the water, the research results of the direct translation and transfer atmospheric scattering target imaging model are still insufficient for underwater detection image enhancement.

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