{'fraction_non_alphanumeric': 0.02378255945639864, 'fraction_numerical': 0.0011325028312570782, 'mean_word_length': 5.646616541353383, '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}}
De-noising and enhancement for SAR oil slick based on SRAD

Synthetic Aperture Radar (SAR) images are extensively used for the determination of oil spill accidents in the marine environment, and oil slick area in SAR image has uneven grayscale, block-shaped dim shadow and the ubiquity of speckle noise, which adversely affect target detection, classification and identification[1]. In order to research on SAR image enhancement, this paper respectively compare Lee filter, Kuan filter, Frost filter and other spatial filtering methods with Speckle Reducing Anisotropic Diffusion (SRAD) algorithm, experimental results show that spatial filtering methods make the edge of the target area blurred which adversely affect the target detection classification and identification, while SRAD algorithm works well de-noising the block-shaped area and has better effect on image enhancement.