{'fraction_non_alphanumeric': 0.022222222222222223, 'fraction_numerical': 0.011555555555555555, 'mean_word_length': 4.519607843137255, '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}}
Prediction of signs of DCT coefficients in block-based lossy image compression

A practical impossibility of prediction of signs of DCT coefficients is generally accepted. Therefore each coded sign of DCT coefficients occupies usually 1 bit of memory in compressed data. At the same time data of all coded signs of DCT coefficients occupy about 20-25% of a compressed image. In this work we propose an effective approach to predict signs of DCT coefficients in block based image compression. For that, values of pixels of already coded/decoded neighbor blocks of the image are used. The approach consist two stages. At first, values of pixels of a row and a column which both are the nearest to already coded neighbor blocks are predicted by a context-based adaptive predictor. At second stage, these row and column are used for prediction of the signs of the DCT coefficients. Depending on complexity of an image proposed method allows to compress signs of DCT coefficients to 60-85% from their original size. It corresponds to increase of compression ratio of the entire image by 3-9% (or up to 0.5 dB improvement in PSNR).