概括
这项研究引入了一种双带除雾模型,以在密的雾中获得更清晰的图像. 它通过单独计算每个频段的传输率来改进现有方法,增强模糊区域的细节.
科学领域:
- 计算机视觉 计算机视觉
- 图像处理 图像处理
- 遥感 遥感 遥感 遥感
背景情况:
- 短波红外 (SWIR) 和可见光融合对于图像脱雾是有效的.
- 现有的方法在密集的雾中扎,依赖于有缺陷的大气散射模型,并假定恒定的可见光透射率.
研究的目的:
- 提出一种新的双带脱雾模型,克服当前融合技术的局限性.
- 通过解决不准确的透射率假设,提高图像除雾性能,特别是在密集的雾条件下.
主要方法:
- 提出了一种双带脱雾模型,使用梯度和和计算聚变重量.
- 发射率为每个频段单独计算,并与融合重量相结合,获得总体加权发射率.
- 该模型的性能与单带传输率模型和SWIR融合算法进行了评估.
主要成果:
- 拟议的双带模型有效地提高了模糊区域的细节,并改善了前景处理.
- 主观的视觉评估和客观的无参考图像质量评估 (NR-IQA) 证实了该模型的优势.
- 新模型的性能优于三个单频传输率模型和八个SWIR融合算法.
结论:
- 拟议的双频脱雾模型在现有图像脱雾技术上提供了显著的进步.
- 这种方法在具有挑战性的雾条件下提供了更好的细节保存和前景清晰度.
- 该模型的有效性通过全面的比较分析来验证.
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