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The Rashid-1 rover, being the main component of the Emirates Lunar Mission (ELM) developed by the Mohammed Bin Rashid Space Center (MBRSC), was launched in late 2022 on-board the Hakuto lunar lander. The scientific objectives of the rover were to investigate the regolith formations of our natural satellite and analyze the geology of its landing area. To perform its investigations, Rashid-1 carried two wide-angle cameras (CAM-1 and CAM-2) and a narrow-angle microscope camera (CAM-M) equipped with Bayer color filter arrays. The mission was however unsuccessful due to a lander failure during lunar descent which caused the loss of the payload. Despite this drawback, significant insights into exploration rover imaging have been gained through the extensive work done prior to launch to achieve the highest image quality from the on-board cameras, and the resulting CASPIP software package will be used for upcoming rover missions. This paper presents the CAM-1 and CAM-2 instruments and the planned advanced image products. In the first part, we provide a detailed presentation of the calibration of the instruments including their optical parameters, characterization of the detector in term of flat-field, optical ghosts, dark current, spectral sensitivities and distortion. The second part of the paper deals with colorimetry, focusing on the colorimetric characterization of the instrument as well as a description of the correction applied to obtain images expressed in the standard color space CIE XYZ and displayed properly in sRGB. Finally, the third part describes advanced image products developed to assist experts (geologists, navigation engineers). It includes a tool for distance visualization directly inside an image, and the creation of 3D images through stereoscopic reconstruction. [ABSTRACT FROM AUTHOR]

Generating mosaics of orthorectified remote sensing images is a challenging task because of the colorimetric differences between adjacent images introduced by land use, surface illumination, atmospheric conditions, and sensor. Most of the existing color correction methods involve pairwise techniques, which are limited when the collection of images is large with numerous overlaps. Besides, available techniques do not operate in a color space suited for true-color processing. This paper presents a simple and robust method to perform the global colorimetric harmonization of multiple overlapping remote sensing images in natural colors (RGB). Our parameter-free method deals simultaneously with any number of images, with any spatial layout, and without any single reference image. It is based on the resolution of a quadratic programming (QP) optimization problem. It operates in the \bml\boldsymbol\alpha\beta decorrelated color space, which is well suited for human vision of natural scenes. The results obtained from the mosaicking of 132 RapidEye color orthoimages over mainland France demonstrate good potential for performing colorimetric harmonization automatically and effectively. [ABSTRACT FROM PUBLISHER]