{'fraction_non_alphanumeric': 0.023046092184368736, 'fraction_numerical': 0.0, 'mean_word_length': 5.445161290322581, '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}}
LANDSAT satellite image fusion metric assessment

Image fusion is an important component of many applications such as inspection, night vision, medical diagnosis, and electro-optical (multispectral) targeting. In this paper, we build upon our previous results for image fusion metrics by applying the methods to satellite imagery versus night vision (visual and infrared imagery) and single-metric biomedical image fusion analysis. Multispectral examples include satellite imagery for land-cover analysis. In this paper, we explore a variety of metrics that have been used to quantify the performance of the fused image products. The exhaustive conclusive analysis over all possibilities is not realizable, so in this paper we group the various metrics into categories and demonstrate an application of the metrics to satellite LANDSAT imagery using an entropy-based image fusion method. From the many metrics analyzed, we found the Image Structural Similarity Based (ISSB) metrics are most useful.