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.

中文翻译：

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幻觉压缩人脸图像

提出了一种人脸幻觉算法，通过将去块的人脸图像分解为结构区域（如面部成分）和非结构区域（如背景），从 JPEG 压缩的低分辨率输入生成高分辨率图像。对于结构区域，地标用于根据估计的头部姿势和光照条件在大型数据集中检索足够的高分辨率组件示例。对于非结构区域，应用高效的通用超分辨率算法来生成高分辨率对应物。将从这两个区域中提取的两组梯度图结合起来以指导生成幻觉图像的优化过程。