Abstract
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
Abstract (translated)
嗨，HiRISE（高分辨率成像科学实验）是一种安装在火星侦察轨道器上的相机，负责在火星表面拍摄前所未有的详细照片。它可以在几秒钟内捕捉到数百万张令人惊叹的近景照片。然而，火星经常受到区域和局部沙暴的困扰，这会阻碍数据收集过程和管道，导致努力和关键飞行时间的损失。通过使用在Resnet-50上微调的Dust Image Classifier自动过滤这些受大气尘埃影响的图像，我的算法可以实现94.05%的准确率。为了进一步简化图像的过滤，我还设计了一个预测管道，该管道对图像进行分类并存储这些沙尘斑块。为了消除部分受阻图像，我还使用基于自动编码器的去噪算法和Pix2Pix GAN，其SSIM指数分别为0.75和0.99。
URL
https://arxiv.org/abs/2405.04807
