Automatic processing of satellite laser ranging data based on image denoising technique.

Satellite Laser Ranging (SLR) data are typically pre-processed involves the manual screening method. However, this methodology heavily depends on the interpreter's expertise, potentially leading to concerns regarding decreased detection efficiency, limited automation, and sluggish processing speeds. This study introduces an automated processing approach using image denoising techniques. It involves deriving binary images from raw SLR point cloud data, employing a median filter to remove noisy data, and generating SLR normal points automatically for accurate and efficient data processing. Theoretical and experimental results reveal that the proposed method exhibits an efficient echo data recognition rate exceeding 80%, while maintaining a low misdetection rate of 1% or less. The proposed method offers a superior alternative to manual screening, capable of processing SLR data in batches, which fulfilling the future need for efficient automation and management of massive SLR datasets. [ABSTRACT FROM AUTHOR]