{'fraction_non_alphanumeric': 0.028026905829596414, 'fraction_numerical': 0.0, 'mean_word_length': 5.765151515151516, '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}}
Motion and edge adaptive interpolation de-interlacing algorithm

This paper presents a new motion and edge adaptive de-interlacing algorithm, which is efficient and artifacts-free. It is novel in the sense that it introduces a way to properly interpolate the two (odd and even) field images according to the information provided by the simplest form of motion detection and edge orientation estimation methods. The proposed algorithm was evaluated by three video sequences, namely, "Akiyo", "Silent", "Foreman". Experimental results confirm that the proposed algorithm performs, both objectively and subjectively, much better than other similar algorithms. These promising results indicate that the proposed interpolation approach has good potential to realize even better de-interlacing algorithms, if more sophisticated motion detection and edge orientation estimation methods are employed.