{'fraction_non_alphanumeric': 0.011597938144329897, 'fraction_numerical': 0.003865979381443299, 'mean_word_length': 4.976923076923077, '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}}
Internal waves detection from ERS-1 SAR images using the 2-D wavelet transform

The utility of wavelet analysis as a tool for automatic oceanic internal wave detection from SAR ocean images is examined using the 2D wavelet transform. A method for coastline detection based on a sequence of basic-processing procedures followed by a contour tracing algorithm is also introduced in order to have sea-land separation to enhance the internal wave detection problem. Then, the image is wavelet transformed with various scales to finally extract the internal wave structures based on the first and second order statistics. The results from this study show that wavelet analysis is an excellent tool to detect and locate internal waves from SAR ocean images against background noise.