Structure Modeling Activation Free Fourier Network for Spacecraft Image Denoising

TL;DR

The document describes the elsarticle LaTeX class designed for formatting submissions to Elsevier journals, detailing its design goals to minimize package conflicts and ensure broad compatibility. It contrasts elsarticle.cls with the older elsart.cls, highlighting improvements in build basis, front matter handling, and support for multiple publication formats. Installation guidance covers where to obtain the class, how to generate the cls file from the provided dtx, and steps to refresh the TeX file database, along with typical loading options for different submission formats. Overall, the work serves as a practical guide for authors to prepare manuscripts with consistent layout and reliable package integration for Elsevier journals.

Abstract

Spacecraft image denoising is a crucial fundamental technology closely related to aerospace research. However, the existing deep learning-based image denoising methods are primarily designed for natural image and fail to adequately consider the characteristics of spacecraft image(e.g. low-light conditions, repetitive periodic structures), resulting in suboptimal performance in the spacecraft image denoising task. To address the aforementioned problems, we propose a Structure modeling Activation Free Fourier Network (SAFFN), which is an efficient spacecraft image denoising method including Structure Modeling Block (SMB) and Activation Free Fourier Block (AFFB). We present SMB to effectively extract edge information and model the structure for better identification of spacecraft components from dark regions in spacecraft noise image. We present AFFB and utilize an improved Fast Fourier block to extract repetitive periodic features and long-range information in noisy spacecraft image. Extensive experimental results demonstrate that our SAFFN performs competitively compared to the state-of-the-art methods on spacecraft noise image datasets. The codes are available at: https://github.com/shenduke/SAFFN.