High-dynamic-range imaging for cloud segmentation
- 1School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), 639798 Singapore
- 2Advanced Digital Sciences Center (ADSC), University of Illinois at Urbana-Champaign, 138602 Singapore
- 3ADAPT SFI Research Centre, Trinity College Dublin, Ireland
Abstract. Sky–cloud images obtained from ground-based sky cameras are usually captured using a fisheye lens with a wide field of view. However, the sky exhibits a large dynamic range in terms of luminance, more than a conventional camera can capture. It is thus difficult to capture the details of an entire scene with a regular camera in a single shot. In most cases, the circumsolar region is overexposed, and the regions near the horizon are underexposed. This renders cloud segmentation for such images difficult. In this paper, we propose HDRCloudSeg – an effective method for cloud segmentation using high-dynamic-range (HDR) imaging based on multi-exposure fusion. We describe the HDR image generation process and release a new database to the community for benchmarking. Our proposed approach is the first using HDR radiance maps for cloud segmentation and achieves very good results.