A Noise De-Correlation Based Sun Glint Correction Method and Its Effect on Shallow Bathymetry Inversion

Abstract

Sun glint on the sea surface is the unavoidable noise in optical remote sensing images. Water depth retrieval based on optical remote sensing images is vulnerable to sun glint contamination. Different sun glint correction methods and their possible effects on improving the accuracy of optical remote sensing water depth inversion are worth adequately discussing. Considering the problem that traditional sun glint correction methods are not well applied in shallow or turbid water areas, this paper proposes a sun glint correction method based on noise de-correlation (ND-SGC) which is not affected by the essential characteristics of the water body itself and does not require any auxiliary data. In this paper, we analyze the spectral fidelity of remote sensing images by using ND-SGC method and traditional methods for sun glint correction, and compare the accuracy of bathymetry inversion in different water depth cases and between sun glint pixels and sun glint-free pixels. The experimental results indicated that: (1) the ND-SGC method gives different penalty weights to sun glint pixels and sun glint-free pixels, which meaningfully improves the bathymetric inversion accuracy of sun glint pixels and maintains the bathymetric inversion accuracy of sun glint-free pixels, and is applicable to any water depth range; (2) the ND-SGC method improves bathymetric inversion accuracy in the extremely shallow water region (0–2 m) and shallow water region (2–11 m), while the conventional method suppresses bathymetric inversion accuracy in these two water depth ranges; (3) the ND-SGC method maintains the inversion accuracy of the sun glint-free pixels, while the traditional Hedley method and Goodman method increase the mean relative error (MRE) of these pixels by a maximum of 6.7% and 8.8%, respectively; (4) the ND-SGC method preserves the inherent spectral information of the remote sensing image well, while the spectral fidelity index of the images corrected by traditional methods shows a certain degree of distortion of the image’s spectrum.