Underwater image restoration through a combination of improved dark channel prior and gray world algorithms

Due to the absorption and scattering of light caused by particles suspended in water and the variable attenuation of light with different wavelengths, underwater images are typically characterized by low contrast, blurred features, and severe color bias. To improve the quality of underwater images, an underwater image restoration method is proposed. First, based on similarities between the underwater optical imaging model and the atmosphere model, an improved dark channel prior algorithm is used to enhance the original underwater image and an improved gray world algorithm is used to calibrate the image. Then, an improved wavelet fusion algorithm is adopted to combine the results produced by the two algorithms. The experimental results show that the proposed method can effectively improve feature clarity and color accuracy in underwater images with low quality and illumination, resulting in a better visual effect. (C) 2019 SPIE and IS&T