TY - GEN
T1 - Detection and estimation of supra-threshold distortion levels of pictures based on just-noticeable difference
AU - Yang, Kaifang
AU - Wan, Shuai
AU - Wu, Hong Ren
AU - Lin, Weisi
AU - Tan, Damian
AU - Gong, Yanchao
AU - Xie, Leyi
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/4
Y1 - 2017/1/4
N2 - A subjective assessment method is described to determine picture quality levels in the supra-threshold region for processed images, with reference to their original counterparts, based on just-noticeable difference (JND) detection experiment. It has been found that the range of JND levels is dependent on picture contents and can be predicted as a function of texture masking factor computed in the pixel domain. The experimental data obtained also reveal that relationship of JND levels in the supra-threshold region and the MSE (mean squared error) can be approximated by a linear function whose slope is modeled as a function of edge and texture contrast masking factors. The model is devised to predict JND levels which provide subjective picture quality rating discernible by human viewers and can be used for visual quality regulated image/video coding, as well as evaluating the capacity of existing objective metrics in predicting picture quality and/or distortion relative to JND based quality/distortion rating categories.
AB - A subjective assessment method is described to determine picture quality levels in the supra-threshold region for processed images, with reference to their original counterparts, based on just-noticeable difference (JND) detection experiment. It has been found that the range of JND levels is dependent on picture contents and can be predicted as a function of texture masking factor computed in the pixel domain. The experimental data obtained also reveal that relationship of JND levels in the supra-threshold region and the MSE (mean squared error) can be approximated by a linear function whose slope is modeled as a function of edge and texture contrast masking factors. The model is devised to predict JND levels which provide subjective picture quality rating discernible by human viewers and can be used for visual quality regulated image/video coding, as well as evaluating the capacity of existing objective metrics in predicting picture quality and/or distortion relative to JND based quality/distortion rating categories.
KW - Picture distortion measures
KW - Supra-threshold levels
KW - contrast masking
KW - just-noticeable difference (JND) detection
KW - subjective picture quality assessment
UR - https://www.scopus.com/pages/publications/85011056328
U2 - 10.1109/VCIP.2016.7805539
DO - 10.1109/VCIP.2016.7805539
M3 - 会议稿件
AN - SCOPUS:85011056328
T3 - VCIP 2016 - 30th Anniversary of Visual Communication and Image Processing
BT - VCIP 2016 - 30th Anniversary of Visual Communication and Image Processing
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 30th IEEE International Conference on Visual Communication and Image Processing, VCIP 2016
Y2 - 27 November 2016 through 30 November 2016
ER -