# A Research and Strategy of Remote Sensing Image Denoising Algorithms

## TL;DR

This paper investigates the suitability of advanced remote sensing image denoising algorithms for satellite onboard processing, proposing two feasible strategies tailored to limited satellite computing resources.

## Contribution

It analyzes existing high-performance denoising methods for their applicability to satellite environments and proposes two new strategies based on TianZhi-1 satellite data.

## Key findings

- High-performance denoising methods often require extensive resources.
- Simulation shows certain methods are suitable for satellite use.
- Two new denoising strategies are proposed for satellite implementation.

## Abstract

Most raw data download from satellites are useless, resulting in transmission waste, one solution is to process data directly on satellites, then only transmit the processed results to the ground. Image processing is the main data processing on satellites, in this paper, we focus on image denoising which is the basic image processing. There are many high-performance denoising approaches at present, however, most of them rely on advanced computing resources or rich images on the ground. Considering the limited computing resources of satellites and the characteristics of remote sensing images, we do some research on these high-performance ground image denoising approaches and compare them in simulation experiments to analyze whether they are suitable for satellites. According to the analysis results, we propose two feasible image denoising strategies for satellites based on satellite TianZhi-1.