Depth based super-resolution for multiview images

Pallavi D. Chavanke, Supriya S. Thombre
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Abstract

Increasing sharpness and visual quality of a low resolution image is an important task in a multiview image processing domain. By using super-resolution approach for multiview images in a mixed resolution setup, quality of a low resolution view will be improved. Firstly, registration of an image is done, to find correspondence between the pixels in different view images. High frequency content generated from high resolution reference images is used to refine the target image with the help of depth map. Depth map calculated by stereo matching algorithm. Finally, Super resolution algorithm is used for multiview images with the help of depth map of a reference images.
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基于深度的多视图图像超分辨率
提高低分辨率图像的清晰度和视觉质量是多视点图像处理领域的一项重要任务。通过在混合分辨率设置下对多视图图像进行超分辨率处理,可以提高低分辨率图像的质量。首先,对图像进行配准,找出不同视图图像中像素之间的对应关系。利用高分辨率参考图像生成的高频内容,借助深度图对目标图像进行细化。采用立体匹配算法计算深度图。最后,借助参考图像的深度图,将超分辨率算法应用于多视图图像。
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