{'fraction_non_alphanumeric': 0.028712871287128714, 'fraction_numerical': 0.0049504950495049506, 'mean_word_length': 5.39873417721519, '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}}
The application of wavelet transform for oceanic feature detection in SAR and optical image

Wavelet transform has been applied for multi resolution analysis of oceanic feature in ERS1/2 SAR and ASTER image data over the Tsushima Strait. Various wavelet transforms, e.g. Haar, Daubechies, Symlet, Coif, Biorthogonal, and Meyer wavelet, have been tested comparably with different level of synthesized image on horizontal, diagonal, and vertical detail, and approximation to study the internal wave characteristic in image. The results show that higher scale processing of image and higher number of vanishing moments of wavelet function such as Coiflet wavelet, coif5, Daubechies wavelet, db5, Symlet wavelet, sym8, and Discrete Meyer wavelet, are proposed for smoother wave crest. The best result of detection is performed by Discrete Meyer wavelet transform, which adapts FIR filter, orthogonal and biorthogonal basis. Thus, it liable for smoothness of feature, space save coding and avoid dephasing in image.