针对高动态范围的红外图像动态范围压缩和细节增强问题, 文中采用基于基层-细节分层处理融合的增强框架, 提出基于拉普拉斯滤波器的基层处理方法, 将高动态红外图像的动态范围压缩到可显示的低动态范围图像, 同时保留图像局部对比度。针对图像中的细节分量, 提出对原始输入高动态范围红外图像提取梯度信息并做非线性增强, 然后将低动态范围图像与增强的梯度信息通过优化融合重建, 得到细节增强的红外图像。实验结果表明, 新算法有效地提高了红外图像的整体对比度, 保留图像的细节信息, 有较佳的图像视觉表现。

Aiming at the subject that compression and enhancement for high-dynamic-range infrared images, a new enhancement framework that based on base-detail layers separation is proposed. Firstly, the dynamic range of the infrared images is compressed by using a Laplacian filter to a low dynamic range image that can be displayed, secondly, the gradient information is extracted from the original high dynamic range infrared images, then the low dynamic range image is combined with the gradient information of the image to optimize the reconstruction. Finally, the infrared images details are enhanced. The experimental results show that the new algorithm can effectively improve the overall contrast of the image and keep the details with better subjective visual perception.