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Banana disease detection by fusion of close range hyperspectral image and high-resolution RGB image

Abstract:

Early detection of banana disease can limit the spread of disease, as well as reduce the treatment costs. Current methods focus on either manually interpretation or calculation of spectral indices (e.g., the normalized difference vegetation index). In this paper, we exploit the fusion of close range hyperspectral (HS) image and high-resolution (HR) visible RGB image for potential disease detection in banana leaves. Our approach applies the joint bilateral filter to transfer the textural structures of HR RGB image to low-resolution HS image and obtain an enhanced HS image. Initial experimental results on Musa acuminata (banana) leaf images demonstrate the efficiency of our fusion approach, with significant improvements over either single data source or some conventional methods.