{'fraction_non_alphanumeric': 0.021479713603818614, 'fraction_numerical': 0.010739856801909307, 'mean_word_length': 5.2611940298507465, '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}}
Modified invariant colour model for shadow detection

High-resolution satellite images usually contain a significant amount of shadow cast by elevated objects. Image information is affected by such shadows. Shadows obscure image information partially and/or totally, which leads to interpretation errors. This article aims to develop a complete shadow detection approach using all available bands of a multispectral image. Therefore, the near-infrared band is employed in addition to visible bands while generating a C1C2C3 colour model to achieve a modified C3 index. A comparative study is then applied to the original C1C2C3, hue, saturation, and value colour model and the modified model, to validate the developed index. The results show the superiority of the proposed approach in shadow detection, with overall accuracy around 94%.