Abstract
The outdoor images captured in sand dust weather often suffer from poor contrast and color distortion, which seriously interfere with the performance of intelligent information processing systems. To solve the issues, a novel enhancement algorithm based on fusion strategy is proposed in this paper. It includes two components in sequence: sand removal via the improved Gaussian model-based color correction algorithm and dust elimination using the residual-based convolutional neural network (CNN). Theoretical analysis and experimental results show that compared with the prior sand dust image enhancement methods, the proposed fusion strategy can effectively correct the overall yellowing hue and remove the dust haze disturbance, which provides a constructive idea for the future development of sand dust image enhancement.
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