LunaXplore enhances low-light images from the PSR regions of lunar craters to improve signal-to-noise ratio (SNR). By applying advanced deep learning and image processing techniques, the project creates high-resolution image maps from Chandrayaan-2's OHRC, aiding lunar landing site selection and supporting geomorphological studies of the lunar pole
python opencv deep-learning hpc tensorflow keras image-processing gan signal-to-noise-ratio retinex-theory
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Updated
Jan 8, 2025