{'fraction_non_alphanumeric': 0.016, 'fraction_numerical': 0.002285714285714286, 'mean_word_length': 5.687022900763359, '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}}
Hyperspectral Image Compression Based on Wavelets and Uniform Directional Filter Banks

A multiscale geometric analysis method based on Wavelet and Uniform Directional Filter Banks (WUDFB) is structured in order to overcome the insufficiencies of contourlet transform and wavelet-based contourlet transform which are used in compression. A novel WUDFB-based compression algorithm of hyperspectral imagery is proposed, in which intra-band WUDFB and inter-band prediction are used to remove the spatial and spectral redundancy respectively, and no-list set partitioned embedded block coder makes output embedded stream. The experimental results by using 64 band hyperspectral data show that the algorithm achieves higher peak signal-to-noise ratio at high compression ratio and preserves more detail information of original images than the algorithm based on wavelet transform.