{'fraction_non_alphanumeric': 0.020442930153321975, 'fraction_numerical': 0.0, 'mean_word_length': 5.125, '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}}
Image fusion based on level set segmentation

Most of image fusion techniques utilize a key notion called “decision map”. This map determines which information to take at what place and therefore governs the fusion process. We illustrate that calculation of decision maps is identical to a segmentation problem. Modifying a state-of-the-art segmentation procedure based on level sets, we obtain more accurate and smooth decision maps. Verification of the proposed method is carried out on wavelet-based multifocus fusion and concluded with an experiment on microscopic multifocal images.