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International Journal of Computer Vision

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08-12-2017

Hallucinating Compressed Face Images

Authors: Chih-Yuan Yang, Sifei Liu, Ming-Hsuan Yang

Published in: International Journal of Computer Vision | Issue 6/2018

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Abstract

A face hallucination algorithm is proposed to generate high-resolution images from JPEG compressed low-resolution inputs by decomposing a deblocked face image into structural regions such as facial components and non-structural regions like the background. For structural regions, landmarks are used to retrieve adequate high-resolution component exemplars in a large dataset based on the estimated head pose and illumination condition. For non-structural regions, an efficient generic super resolution algorithm is applied to generate high-resolution counterparts. Two sets of gradient maps extracted from these two regions are combined to guide an optimization process of generating the hallucination image. Numerous experimental results demonstrate that the proposed algorithm performs favorably against the state-of-the-art hallucination methods on JPEG compressed face images with different poses, expressions, and illumination conditions.

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Title: Hallucinating Compressed Face Images
Authors: Chih-Yuan Yang
Sifei Liu
Ming-Hsuan Yang
Publication date: 08-12-2017
Publisher: Springer US
Published in: International Journal of Computer Vision / Issue 6/2018
Print ISSN: 0920-5691
Electronic ISSN: 1573-1405
DOI: https://doi.org/10.1007/s11263-017-1044-4

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