{'fraction_non_alphanumeric': 0.02924791086350975, 'fraction_numerical': 0.01532033426183844, 'mean_word_length': 4.845528455284553, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A Low-Rank Method for Sentinel-2 Sharpening Using Cyclic Descent

Multiresolution optical remote sensing systems often have a spatial resolution that varies between bands. An example is the Sentinel-2 (S2) constellation which has three levels of spatial resolution 10m, 20m, and 60m. Recently, researchers have exploited the spectral/spatial correlation inherent in multispectral data to sharpen the lower resolution S2 bands. In this paper, we propose a low-rank method that formulates the sharpening process as a solution to a cost function. We develop an iterative algorithm based on cyclic descent and call it S2Sharp-CD. We evaluate the method on a simulated dataset and compare it to a state-of-the-art approach.