高动态范围成像通常需要利用多个不同曝光时间的低动态范围图像来合成高动态范围图像。在合成后图像噪声会进一步放大，可能导致最终的高动态范围图像视觉质量严重降低。针对合成图像需要保留低曝光图像中高亮区域的细节信息以及高曝光图像中低暗区域的细节信息，且图像噪声与亮度有关这一问题，本文提出一种基于亮度分区、噪声水平估计的高动态范围图像融合过程中的噪声抑制算法。首先，根据图像的亮度信息，确定低动态范围图像的不同亮度区域；然后对图像不同亮度区域，利用重叠块估计噪声水平，根据得到的噪声水平，指导图像的稀疏去噪；最后，对处理后的低动态范围图像，采用融合方法合成高动态范围图像。实验结果表明，所提出的算法能有效地抑制图像噪声，合成的高动态范围图像具有更好的视觉质量。

A high dynamic range image is generated by using multiple low dynamic range images with different exposure times. After the generation, the image noise will be further amplified, resulting in a severe degradation in the visual quality of the final high dynamic range image. In view of the problem that the generated image needs to retain the detail information of the high-lighted area in the low-exposure image and the detail information of the low-dark area in the high-exposure image and the image noise is related to the luminance, a noise suppression algorithm based on luminance partitioning and noise level estimation in the process of high dynamic range image fusion is proposed in this paper. Firstly, according to the luminance information of the image, different luminance regions of the low dynamic range image are determined. And then the overlapped blocks are used to estimate the noise level of the different luminance regions of the image, so as to guide the sparse denoising of the image. Finally, a high dynamic range image is generated by the processed low dynamic range images. The experimental results show that the proposed algorithm can effectively suppress noise, and the generated high dynamic range image has better visual quality.