Image restoration using digital inpainting and noise removal
Image restoration using digital inpainting and noise removal
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DOI：
10.1016/j.imavis.2005.12.008
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发表时间：
2007
期刊：
影响因子：
--
通讯作者：
C. Barcelos;M. A. Batista
中科院分区：
文献类型：
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作者：
C. Barcelos;M. A. Batista
图像修复和去噪是图像处理领域的两个重要任务，在图像和视觉分析中有着广泛的应用。在本文中，我们提出了一种新的方法来恢复图像。我们的方法在去除噪声的同时填充丢失、损坏或不期望的信息。去噪是通过在修复域内部和外部工作的平滑方程来执行的，但方式完全不同。在修复域内部，平滑由平均曲率流执行，而修复域外部的平滑以鼓励区域内的平滑并阻止跨边界的平滑的方式执行。除了平滑之外，这里提出的方法允许将可用信息从外部传输到修复域的内部。这种组合允许同时使用图像的不同区域的填充和差分平滑。实验结果表明，这两个程序的组合在恢复划伤的照片，disocclusion（或从图像中删除整个对象）的视觉分析和文本从图像中删除的有效性能。
Inpainting and denoising are two important tasks in the field of image processing with broad applications in image and vision analysis. In this paper, we present a new approach for image restoration. Our method simultaneously fills in missing, corrupted, or undesirable information while it removes noise. The denoising is performed by the smoothing equation working inside and outside of the inpainting domain but in completely different ways. Inside the inpainting domain, the smoothing is carried out by the Mean Curvature Flow, while the smoothing of the outside of the inpainting domain is carried out in a way as to encourage smoothing within a region and discourage smoothing across boundaries. Besides smoothing, the approach here presented permits the transportation of available information from the outside towards the inside of the inpainting domain. This combination permits the simultaneous use of filling-in and differentiated smoothing of different regions of an image. The experimental results show the effective performance of the combination of these two procedures in restoring scratched photos, disocclusion (or removal of entire objects from the image) in vision analysis and text removal from images.