Comparative study on hyperspectral image enhancement for low illumination outdoor scenes images - Quan, Lee Yong; Rohana, Abdul Karim; Nurul Wahidah, Arshad; Nor Farizan, Zakaria; Wan Nur Azhani, Wan Samsudin; Yasmin, Abdul Wahab; Saputro, Adhi Harmoko (Springer Science and Business Media Deutschland GmbH, 2022)
Hyperspectral image is rich with information because it contains spatial and spectral properties of specific objects. However, the image quality may be affected by low lighting conditions caused by non-uniform illumination environments, uncontrollable weather, which tends to darken outdoor scenes. Difficulty arises for high order image processing modalities such as detection, classification and tracking. In this paper, a comparative study was conducted to identify the most appropriate enhancement method for outdoor scenes. Four techniques were investigated: Bio-Inspired Multi-Exposure Fusion (BIMEF), Dehazing, Illumination Estimation, and Multi-deviation Fusion (MF). Experiments revealed that BIMEF is the best approach with the lowest lightness of error.