@inproceedings{838d8248cc8143ad9de40bd406fdbc49,
title = "Mode-dependent distortion modeling for H.264/SVC coarse grain SNR scalability",
abstract = "This paper presents a mode-dependent distortion model for H.264/SVC coarse grain SNR scalability. It estimates the base-layer and enhancement-layer's distortions with particular consideration of their prediction modes and inter-layer residual prediction. Based on a parametric signal model, the variances of the transformed prediction residual at both layers are first formulated analytically and approximated empirically. The results are then incorporated into the assumption that the transform coefficients are distributed according to the Laplacian distribution to obtain the final distortion estimates. Experimental results confirm its fairly good ability to predict the actual distortions in both the frame and macroblock levels.",
keywords = "coarse grain SNR scalability, distortion modeling, Scalable video coding",
author = "Jian, {Yin An} and Chen, {Chun Chi} and Wen-Hsiao Peng",
year = "2014",
month = jan,
day = "28",
doi = "10.1109/ICIP.2014.7025640",
language = "English",
series = "2014 IEEE International Conference on Image Processing, ICIP 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3165--3169",
booktitle = "2014 IEEE International Conference on Image Processing, ICIP 2014",
address = "United States",
}