{'fraction_non_alphanumeric': 0.01519213583556747, 'fraction_numerical': 0.008936550491510277, 'mean_word_length': 4.925925925925926, '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}}
Multi Modal Image Fusion: Comparative Analysis

Image fusion acts as a powerful tool in the medical domain. It is an essential method for enhancing the quality of images by combining the complementary images which are captured from various sensors or cameras. The aim of multi modal image fusion technique is to obtain a single fused image by fusing the images of different modalities. It is widely used in various clinical applications for better diagnosis of several types of diseases. In this paper, comparative analysis has been made using various multi modal techniques in medical domain such as guided filter, multi resolution singular value decomposition and principal component analysis. The quantitative and qualitative results have been taken. The experiment results indicated that guided filter method is more efficient as compared to other methods in terms of evaluation metrics such as standard deviation is 29.8, mean is 52.3, entropy is 2.8 and fusion information score is 0.8. It has also been observed that guided filter is able to preserve edges efficiently and is more suitable for real applications.