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Face Hallucination under an Image Decomposition Perspective

机译:在图像分解视角下面对幻觉

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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,我们建议将面部幻觉的任务转换为图像分解问题,然后使用形态分量分析(MCA)来基于新颖的三步框架来幻觉。首先,通过插值采样低分辨率输入图像。然后,使用MCA来将内插图像分解为高分辨率图像,并且由于MCA可以根据典型词典将信号正确分解为特殊部分。最后,执行基于邻居修补的残余补偿,以增强面部细节。该方法可以在图像分解视角下有效利用面部性能的面部性能。实验结果表明了我们方法的有效性,就幻觉脸部图像的视觉质量而言。

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