{'fraction_non_alphanumeric': 0.011024643320363165, 'fraction_numerical': 0.0019455252918287938, 'mean_word_length': 5.297959183673469, '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}}
A Perceptually Optimized Embedded Image Coder and Quality Assessor Based on Visual Tools

In this paper, we propose a new Perceptually Optimized Embedded ZeroTree Image Coder EVIC and Quality Assessor WVDP. The coder introduces a perceptual weighting to wavelet coefficients prior to control SPIHT encoding algorithm in order to reach a targeted bit rate with a perceptual quality improvement with respect to the coding quality of the SPIHT algorithm only. The paper also, introduces a new objective quality metric based on Daly visual model known as Visible Difference Predictor that integrates the properties of the HVS and plays an important role in our EVIC quality assessment. Our EVIC coder is based on a vision model that incorporates various masking effects of human visual system HVS perception. Thus, our coder weights the wavelet coefficients based on that model and enhances the perceptual quality for a given bit rate and observation distance. The model weights within all wavelet sub bands are computed with respect to 1) luminance masking and Contrast masking deployed to ensure threshold elevation, 2) the contrast sensitivity function CSF to filter invisible frequencies, 3) the Just Noticeable Differences JND used to take into account only wavelet coefficients with respect to that perceptual thresholds. The EVIC coder has the same computational algorithm complexity as the standard SPIHT. However, the experimental results show that it demonstrates very good performances in terms of image coding and quality measurement.