{'fraction_non_alphanumeric': 0.008032128514056224, 'fraction_numerical': 0.0, 'mean_word_length': 5.8, '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}}
Construction of intuitionistic fuzzy contrast enhanced medical images

Medical images are poorly illuminated and enhancement is very much essential. Though there are many image enhancement algorithms in literature, but enhancement of medical images is very much difficult. This paper presents a new method using intuitionistic fuzzy set theory for medical image enhancement. The method produces an intuitionistic fuzzy image using Sugeno type fuzzy complement and the parameter in intuitionistic fuzzy image is optimized using intuitionistic fuzzy entropy. Experimental results on several low contrasted medical images show that the proposed method produces better enhanced image as compared to the existing fuzzy and intuitionistic fuzzy methods.