Fusion-based underwater image enhancement by wavelet decomposition

Underwater images suffer from poor visibility due to two main factors: one is the color attenuation caused by light absorption, and the other one is low contrast and blur caused by particles scattering existing in underwater environments. To achieve underwater image enhancement, a fusion-based strategy applied to frequency domain is proposed. The proposed fusion process involves two inputs which are represented as color corrected and contrast enhanced images extracted from original underwater image. Both the color corrected and contrast enhanced images are decomposed into low frequency and high frequency components by three-scale wavelet operator. The low frequency and high frequency components are fused via a multi-scale fusion process. The low frequency components are fused by weighted average, and the high frequency components are fused by local variance. These fused low frequency and high frequency components can be reconstructed as final enhanced image. The experimental results show that the proposed algorithm can improve the visibility of underwater images significantly. In addition, the proposed approach arrives a good result in image feature points detection and matching in underwater environments.