Abstract
Perceptual visibility threshold estimation, based upon characteristics of the human visual system (HVS), has wide applications in digital image/video processing. An improved scheme for estimating just-noticeable distortion (JND) is proposed in this paper. It is proved to outperform the DCTune model, with the major contributions of a new formula for luminance adaptation adjustment and the incorporation of block classification for contrast masking. The HVS visibility threshold for digital images exhibits an approximately parabolic curve versus gray levels and this has been formulated to yield a more accurate base threshold. Moreover, edge regions have been differentiated via block classification to effectively avoid over-estimation of JND in the said regions. Experiments with different images and the associated subjective tests show improved performance of the proposed scheme over the DCTune model for luminance adaptation (especially in dark regions) and masking effect in edge regions. Our model has further demonstrated to achieve favorable results in perceptual visual distortion gauge and image compression. The improvement in JND estimation facilitates better visual distortion measurement and visual signal compression.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.