基于图像融合的自适应水下图像增强

针对水下图像对比度低及细节模糊的问题,提出一种基于图像融合的自适应水下图像增强方法,实现不同类型水下图像的增强效果。基于颜色校正方法对水下图像进行颜色均衡化预处理;对亮度分量L进行Gamma校正,获得对比度提升的亮度图像;对两个亮度分量进行三层小波分解,提出对分解所得的低频分量及高频分量分别采用线性融合和自适应融合策略进行融合。多尺度融合保证了增强图像细节的丰富性,自适应融合策略体现了融合过程的可控性。实验结果表明,增强的水下图像呈现出高对比度和清晰的细节。

Adaptive underwater image enhancement method via image fusion

Aiming at the problem that the underwater image is low-contrast and detail blurred,an adaptive underwater image enhancement method based on image fusion was proposed to improve the performance of different types of underwater images.The underwater image was preprocessed using color correction method.The brightness component L was corrected by Gamma correction to obtain the brightness image with enhanced contrast.The two brightness components were processed by three-layer wavelet transform.After decomposition,the low-frequency component and high-frequency component were fused by linear fusion and adaptive fusion,respectively.Multiscale fusion ensures the richness of image details.The adaptive fusion strategy embodies the controllability of the fusion process.Experimental results show that the enhanced underwater image presents high contrast,balanced saturation and brightness.