计算机科学 ›› 2022, Vol. 49 ›› Issue (1): 187-193.doi: 10.11896/jsjkx.210600090
王以涵, 郝世杰, 韩徐, 洪日昌
WANG Yi-han, HAO Shi-jie, HAN Xu, HONG Ri-chang
摘要： 在暗光或逆光拍照时,获得的图像常常出现过暗或光照分布不均的现象,导致图像视觉质量较差。基于Retinex模型的暗光增强模型能实现有效地光照增强。但此类暗光增强模型也存在一些问题,即待处理图像中暗光区域的可视度虽然得到了有效改善,但其中隐藏的噪声也被放大和凸显,依旧影响了增强结果的视觉质量。为解决这一问题,构建了基于低秩矩阵估计的暗光图像增强模型。首先,构建包含噪声项的Retinex模型并对其进行交替优化,将暗光图像分解为光照层I以及反射层R。在这一过程中,利用低秩矩阵估计实现了对R层的噪声抑制。其次,考虑到在去噪过程中产生的图像细节被模糊的问题,进一步利用光照层I作为导向图,来融合包含和不包含去噪效果的两种增强图像,实现兼顾噪声抑制和图像原有细节保持的效果。与多种类型的暗光增强方法进行对比,所提模型在直观视觉比较和客观量化指标比较方面均取得了较好的结果。
中图分类号:
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