Abstract
The noise correction and image enhancements are done at the Data Processing Generation System (DPGS) at the National Remote Sensing Center (NRSC) satellite data production chain. Even after the noise correction algorithms, pixel noise is observed at the checkout by the Product Quality Control (PQC) system. These are detected manually at PQC and an alert is raised at the DPGS to recorrect the image. This process is time consuming due to the manual intervention and the application of noise correction algorithm on the entire image. This manuscript proposes a novel 2-stage, sliding window-based algorithm to automatically detect pixel noise in satellite images and localise the noise pixels so that the correction algorithms can be applied in a localised fashion. This local noise correction also restores the overall SNR of the image compared to global correction. This algorithm is realized and tested on data obtained from the Indian remote sensing (IRS) satellites like Cartosat-2S, Resourcesat-2/2A. The dataset is not open-sourced, and hence very minimal information is provided regarding the IRS data. However, we use Landsat-8 data to conduct a few analyses on the algorithm's performance. The role of patch size considered during the detection of pixel noise in satellite data is also analyzed.
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