HiRISE (High-Resolution Imaging Science Experiment) is a camera onboard the Mars Reconnaissance orbiter responsible for photographing vast areas of the Martian surface in unprecedented detail. It can capture millions of incredible closeup images in minutes. However, Mars suffers from frequent regional and local dust storms hampering this data-collection process, and pipeline, resulting in loss of effort and crucial flight time. Removing these images manually requires a large amount of manpower. I filter out these images obstructed by atmospheric dust automatically by using a Dust Image Classifier fine-tuned on Resnet-50 with an accuracy of 94.05%. To further facilitate the seamless filtering of Images I design a prediction pipeline that classifies and stores these dusty patches. I also denoise partially obstructed images using an Auto Encoder-based denoiser and Pix2Pix GAN with 0.75 and 0.99 SSIM Index respectively.

翻译：HiRISE（高分辨率成像科学实验）是搭载于火星勘测轨道飞行器上的相机，负责以前所未有的细节拍摄火星表面大片区域，可在数分钟内捕捉数百万张惊人的特写图像。然而，火星频繁发生的区域性和局部沙尘暴会阻碍这一数据采集流程及处理管线，导致人力与关键飞行时间的浪费。人工剔除这些图像需耗费大量人力。本文通过基于ResNet-50微调的尘埃图像分类器，以94.05%的准确率自动过滤这些被大气尘埃遮挡的图像。为进一步实现图像的流畅筛选，我设计了一套预测管线，用于分类并存储这些尘埃斑块。同时，采用基于自编码器的去噪器和Pix2Pix GAN对部分遮挡图像进行去噪处理，其SSIM指数分别为0.75和0.99。