Titlebook: Digital Heritage Reconstruction Using Super-resolution and Inpainting; Milind G. Padalkar,Manjunath V. Joshi,Nilay L. Kha Book 2017 Spring

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Ilona Szőcs,Bodo B. Schlegelmilch when time is of the essence. Another way to find the best-mapped patch for a particular LR patch is to restrict the search space within a neighborhood of the LR patch in the coarser-resolution image. But this may not always result in the best-mapped patch for that particular LR patch.

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Image Super-resolution: Self-learning, Sparsity and Gabor Prior,ails of the skillful historic work. This chapter presents a super-resolution approach for resolution enhancement that exploits the recurrence of the visual content in natural images, which is an important characteristic of the images captured at heritage sites. Glasner et al. [42] have shown that fo

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Attempts to Improve Inpainting,ches and discussed an autoregressive modelbased technique to overcome the limitations. Nevertheless, the technique proposed in Chapter 4 did not deal with the problem of finding good exemplar patches for better inpainting, and instead provided a solution to improve the inpainting using the pixel-nei

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Detecting and Inpainting Damaged Regions in Facial Images of Statues,numents, especially statues, there is a consensus about the desire to view these without any damage to the dominant facial regions. This encourages the exploration for a technique that automatically detects the damaged regions so that their repair can be completely automated using an existing inpain

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Auto-inpainting Cracks in Heritage Scenes,this chapter, we consider the damage in non-facial regions and describe techniques to automatically detect these and inpaint them. In particular, we consider the non-facial region that can have damage like cracked regions. These cracks in a heritage site could be developed over a period of time due