{'fraction_non_alphanumeric': 0.023752969121140142, 'fraction_numerical': 0.004750593824228029, 'mean_word_length': 5.534883720930233, '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}}
Estimating blockness distortion for performance evaluation of picture coding algorithms

Some of the most significant image quality indexes are reviewed and compared with a new method for blockness distortion evaluation. The paper begins with a brief survey on classical measures based on numerical difference between the original and reconstructed image data (e.g., MSE, SNR and PSNR) and advanced methods aiming at considering the perceptive aspects of image degradation (e.g., Hosaka (1986) plots and other methods based on human visual system properties like information content or perceptual image distortion). After, four innovative methods for blockness distortion measurement are proposed: two based on DCT analysis, and two on differential Sobel operator. Results on standard pictures confirm the efficiency of the proposed measures.