IMAGE FUSION WAVLET-BASED SHARPNESS ENHANCEMENT OF LROC WIDE ANGLE CAMERA IMAGES – PERFORMANCE COMPARISON AMONG WAVELET TYPES A. Awumah, P. Mahanti,

Introduction: Image fusion involves integrating elements from two or more characteristically different, multi-sensor, and/or multi-temporal images to create a new image that relays more information than the component images provide. In Earth-based remote sensing, image fusion is employed to enhance the spatial resolution of a multi-spectral (MS) image by integrating the MS spectral content with geometric (edge) details from a higher-resolution panchromatic (Pan) image. The derived high-resolution multispectral (HRMS) image can then be said to have both highspectral (from the original MS) and high-spatial (from the Pan) resolutions. Although widely utilized in Earthbased remote sensing, image fusion as applied to planetary images is still relatively uncommon; a few known applications include its use in Viking Orbiter images of Mars [1,2] and Chandrayaan and SELENE images of the Moon [3]. In the current design of most remote sensing imaging systems, an inherent trade-off exists between a system’s ability to highly resolve spatial and spectral information, due to the standing inverse relationship between the system’s instantaneous field-of-view and spectral bandwidth sizes. Additionally, planetary mission payload mass restrictions, and data transmission and cost limitations make the integration of an on-board HRMS imaging system typically unfeasible. Thus, planetary missions which integrate both low-resolution MS and high-resolution Pan instruments stand to benefit from image fusion as a suitable post processing solution for sharpness enhancement of MS images. Several standard image fusion methods have been developed which establish various means of extracting geometric details from the Pan and injecting it into the MS. While many of these methods are successful at enhancing the spatial resolution of the MS, results may contain significant color distortion. In a previous work, the following six well-known image fusion methods were applied to Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) and Wide Angle Camera (WAC) images: Intensity-HueSaturation, Brovey Transform, Principal Component Analysis, the University of New Brunswick method, High Pass Filter and Additive Wavelet [4]. In both qualitative (via visual inspection) and quantitative (metric-based) assessments in which spectral content preservation was emphasized over sharpness enhancement, the wavelet-based image fusion method yielded the best spectral performance. In this study we apply different wavelet-based image fusion methods to lunar images from the LROC WAC and NAC system based on wavelet family and level of decomposition, and assess results for overall spatial and spectral quality.