A Research and Strategy of Remote Sensing Image Denoising Algorithms
This addresses the challenge of efficient data processing on satellites with limited computing resources, but it is incremental as it adapts existing methods rather than introducing new ones.
The paper tackled the problem of remote sensing image denoising for satellites to reduce transmission waste by evaluating existing ground-based denoising approaches under satellite constraints, and proposed two feasible strategies based on the TianZhi-1 satellite.
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.