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Face Hallucination under an Image Decomposition Perspective

机译:图像分解视角下的幻觉

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In this paper we propose to convert the task of face hallucination into an image decomposition problem, and then use the morphological component analysis (MCA) for hallucinating a single face image, based on a novel three-step framework. Firstly, a low-resolution input image is up-sampled by interpolation. Then, the MCA is employed to decompose the interpolated image into a high-resolution image and an unsharp masking, as MCA can properly decompose a signal into special parts according to typical dictionaries. Finally, a residue compensation, which is based on the neighbor reconstruction of patches, is performed to enhance the facial details. The proposed method can effectively exploit the facial properties for face hallucination under the image decomposition perspective. Experimental results demonstrate the effectiveness of our method, in terms of the visual quality of the hallucinated face images.
机译:在本文中,我们提出将人的幻觉任务转换为图像分解问题,然后基于一种新颖的三步框架,使用形态成分分析(MCA)对单个人脸图像进行幻觉。首先,通过插值对低分辨率输入图像进行上采样。然后,由于MCA可以根据典型词典将信号正确分解为特殊部分,因此可以使用MCA将插值后的图像分解为高分辨率图像和不清晰的蒙版。最终,执行残差补偿,该残差补偿基于斑块的邻近重建,以增强面部细节。在图像分解的角度下,该方法可以有效地利用面部属性进行幻觉。实验结果证明了我们方法在幻觉人脸图像的视觉质量方面的有效性。

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