{'fraction_non_alphanumeric': 0.016928657799274487, 'fraction_numerical': 0.0, 'mean_word_length': 5.624, '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}}
Speckle reduction and linear feature extraction from microwave images using Beamlet Transform

Extracting Linear Features from Microwave Images (SAR) using Beamlet Transform is proposed in this paper. Microwave images are independent of climate. In certain durations these images are affected by noise (Speckle). So Speckle is removed in this work by using Soft threshold technique. For extracting the linear Features, Beamlet Transform based algorithm was applied. This algorithm recursively partitions the image into sub-squares to build a beamlet dictionary to perform the transform followed by discontinuities are linked to extract the linear features. Finally, Experimental results are shows the feature extraction from microwave images using Beamlet Transform to increase the correctness and quality of satellite Mapping.