{'fraction_non_alphanumeric': 0.02188679245283019, 'fraction_numerical': 0.0022641509433962265, 'mean_word_length': 5.314285714285714, '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}}
Weighted Embedded Zero Tree for Scalable Video Compression

Video streaming over the Internet has gained popularity during recent years mainly due to the revival of videoconferencing and videotelephony applications and the proliferation of (video) content providers. However, the heterogeneous, dynamic, and best-effort nature of the Internet cannot always guarantee a certain bandwidth for an application utilizing the Internet. Scalability has been introduced to deal with such issues (up to a certain point) by intelligently separating any information stream into multiple streams. The reception of one, several, or all stream influences the perceived quality of the information as basic, improved, or best, respectively. In addition, wavelet-based scalability combined with representation methods such as embedded zero trees (EZWs) improves the decode-ability of the stream even when only the initial part of the streams have been received. In this paper, we propose a method to improve on the compression rate of the EZW for scalability purposes by reducing the number of levels used in the tree. Therefore, the proposed method should be able to deal more efficiently with the mentioned scalability issues in low bandwidth network. Initial experimental show that the first two layers of the generated EZW are about 22.6%