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    基于小波图像融合的表情细节合成

    Expression Detail Synthesis Based on Wavelet-Based Image Fusion

    • 摘要: 表情细节是人脸表情变化时带来的皮肤纹理变化,表情细节合成有助于增强合成表情的真实感.提出了基于小波的图像融合方法,挖掘表情细节的纹理特征本质,并应用到表情细节的合成中,使合成的表情更加真实自然.为了满足表情细节个性化的需求,采用传统的小波变换和双树复小波变换,同时使用不同的融合算子,得到了丰富的表情合成.本方法不仅适用于灰度图像,通过颜色空间的转换还适用于彩色图像.最后还提出了基于聚类和图切割的最优替换区域选取方法,使得合成的表情细节区域与目标图像融为一体.

       

      Abstract: Expression details are texture changes caused by facial expression, such as wrinkles in the corner of the mouth when smiling and wrinkles on the forehead when surprising. Expression details can help to enhance the realistic experience of synthesized face image. In this paper, we propose to synthesize expression details by using the method of wavelet-based image fusion. We try to mine the texture feature of expression details for natural expression generation. In order to meet the requirements of individual expression detail synthesis, we use different wavelet transforms, such as the traditional wavelet transform and dual-tree complex wavelet transform, and kinds of fusion operators to get rich results. To seamlessly integrate the synthesized image of expression details to the output expressive face image, we select the optimal replacement for both images by clustering and graph cut method. Our proposed approach is applied to not only grayscale images, but also color images by the color space conversion. The experimental results show that the proposed method is effective on the expression detail synthesis, which can enhance the realistic experience of synthesized face image.

       

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