摘要
针对雾霾等恶劣天气导致户外图像降质的问题,设计了一种简单、高效的图像去雾算法。首先通过空域高通滤波对降质图像进行处理,达到压制低频分量、增强图像边缘细节的目的;然后,对滤波后的图像进行空间线性对比度拉伸,增强图像的对比度;最后通过拉普拉斯金字塔的多曝光图像融合方法,将滤波结果与对比度拉伸结果进行融合,得到最终的去雾图像。实验结果表明,所提算法实时性较高,对雾霾、沙尘、水下等降质图像均有较好的增强效果。
Outdoor images captured in bad weather often have poor qualities in terms of visibility and contrast. A simple and effective algorithm was designed to remove haze. Firstly, the spatial high-pass filtering was used to suppress the low- frequency component and enhance the edge detail, and then the contrast-stretching transformation was used to acquire an image with high dynamic range. Finally, the exposure fusion method based on Laplacian pyramid was utilized to fuse the two results above and get the defogged image. The experimental results show that the proposed method has a good performance on enhancing images that are degraded by fog, dust or underwater and it is appropriate for real-time applications.
出处
《计算机应用》
CSCD
北大核心
2014年第3期820-823,共4页
journal of Computer Applications
基金
国家自然科学基金资助项目(61272043)
应急通信重庆市重点实验室开放课题项目(20120504)
关键词
图像去雾
空域高通滤波
曝光融合
image dehazing
spatial high-pass filtering
exposure fusion
