Abstract
The microwave remote sensing system is the broadest tool use to get information about the earth's objects in the form of images. These images are very much affected by various noises, which affects the precision of the images. These, in turn, affect the information present in it. To improve, the quality of satellite images, denoising of the image is an essential task. Gaussian noise majorly seen in all remotely sensed images. Natural sources cause this noise during the acquisition of the image. Many Researchers used Numerous types of filtering techniques to reduce such noises. In this paper, we have focused on lowering Gaussian noise from the microwave satellite dataset. To minimise Gaussian noise, the spatial domain Gaussian Low Pass Filter (GLPF) with different window sizes applied to a single Polarized (HH) L-band ALOS PALSAR satellite SLC level-1 Datasets. The results of filtered images are evaluated based on the respective mean, standard deviation and coefficient of variance.
)