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.