Lunar Turing-GAN Super-Resolution Model

Objective: Create a high-resolution map of the Moon using a pipeline of Image Super-Resolution models

  1. Proposed a novel GAN-based architecture with separate adversaries for ensuring accurate reconstruction of craters and hills
  2. Developed a Lunar Atlas by correcting coordinates & stitching together individual image patches from Chadrayaan-2 TMC payload
  3. Created a pipeline capable of tiling and super-resolving an image using Lunar T-GAN, HAT, RealESRGAN and sharpening algorithms
  4. Achieved a competitive SSIM of 0.794 while increasing spatial resolution from 5m/pixel to 30 cm/pixel, a 16x magnification

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