A non-uniform illumination image enhancement method based on fusion of events and frames

The dynamic range of standard frame-based cameras is much smaller than that of natural scenes. Images captured by standard cameras in non-uniform illumination scenes may be over-exposure, under-exposure, or a combination of both, limiting the visibility of the images. Enhancing images with uneven illumination is a tough assignment. Although most of the existing non-uniform illumination image enhancement methods can preserve details well in dark areas, they cannot regain details in bright regions and may produce noise and halos. Event cameras have a higher dynamic range and are less affected by scene lighting than standard cameras. In this paper, we utilize the complementary advantages of event cameras and standard cameras to improve the visibility of unevenly illumination images, enhance the brightness of dark areas, and recover details in bright areas. First, events and frames are converted into intensity frames by corresponding preprocessing methods, which are subjected to a gamma correction operation to obtain artificial multi-exposure image sequences. Then, the weight map of each artificially exposed image is designed using several evaluation terms, namely contrast, well-exposure, and average brightness. After that, the weight terms are combined with the Laplacian pyramid algorithm to get a fused image. Finally, the final image is created by color restoration and contrast enhancement. Quantitative and qualitative experimental results demonstrate that our method enhances the details and visibility of non-uniform illumination images more effectively than several contrast algorithms.