Labeled dataset for training despeckling filters for SAR imagery.

ABSTRACT: When training Artificial Intelligence and Deep Learning models, especially by using Supervised Learning techniques, a labeled dataset is required to have an input with data and its corresponding labeled output data. In the case of images, for classification, segmentation, or other processing tasks, a pair of images is required in the same sense, one image as an input (the noisy image) and the desired (the denoised image) one as an output. For SAR despeckling applications, the common approach is to have a set of optical images that then are corrupted with synthetic noise, since there is no ground truth available. The corrupted image is considered the input and the optical one is the noiseless one (ground truth). In this paper, we provide a dataset based on actual SAR images. The ground trut

SUBMITTER: Vasquez-Salazar RD 

PROVIDER: S-EPMC10838683 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature