{'fraction_non_alphanumeric': 0.021711366538952746, 'fraction_numerical': 0.005108556832694764, 'mean_word_length': 5.173228346456693, '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}}
Median-based post-processing for VQ image transmission over noisy channels

For image transmission over noisy channels, the VQ paradigm is a strong competitor. We propose a post-processing scheme that is able to improve the perceptual quality of the VQ reconstructed image, for various types of noisy channels, when it is combined with an appropriate index assignment. For binary symmetric channels, we use the index assignment resulting from the Linde, Buzo and Gray (1980) LBG design of the codebook, which ensures a low channel distortion. For the more challenging case of memory channels we consider index assignments specifically designed. We show that a significant perceptual improvement can be achieved with our post-processing scheme both for memoryless and memory channels.