Abstract
Image inpainting is a process of reconstructing damaged or missing part of an image. Initially the work of restoration was performed by skilled artists and was limited to paintings and other artwork of eminence but this process was very tedious and strenuous and therefore digital image inpainting was introduced. The application of inpainting in reconstruction of heritage images is garnering a lot of attention from researchers. The reconstruction of heritage images using inpainting poses a challenging task because of its very high resolution and high meaning full structure content. In traditional exemplar based algorithms the patch with the minimum distance or high similarity may not always be the best match patch. One of the characteristic functions of the Intuitionistic fuzzy set is its definition of degree of hesitancy. In the proposed paper this concept is used to find best exemplars. The mathematical model of intuitionistic fuzzy set is studied and a modified exemplar algorithm based on Intuitionistic fuzzy sets is proposed to solve image inpainting problem. The proposed intuitionistic based inpainting algorithm is applied to heritage images. The results are compared with existing and earlier proposed algorithms on the basis of subjective inpainting quality assessment method
Highlights
Image inpainting is a process of reconstructing damaged or missing part of an image
The inpainting technique can be categorized broadly as Diffusion based and Exemplar based on the basis of image priors such as smoothness priors, self similarity prior and sparse priors
Different variations of higher order fuzzy sets have been proposed by many researchers motivated from Zadeh‟s proposed fuzzy sets (FSs) theory [11]
Summary
Image inpainting is a process of reconstructing damaged or missing part of an image. Initially the work of restoration was performed by skilled artists and was limited to painting and other artwork of eminence but this process was very tedious and strenuous and digital image inpainting was introduced. The inpainting technique can be categorized broadly as Diffusion based and Exemplar based on the basis of image priors such as smoothness priors, self similarity prior and sparse priors In these methods an assumption is made that the known pixels and unknown pixels of the images have same geometrical structures or statistical properties. The exemplar based inpainting approach considers both structural and textural information of image while filling up target region. As the algorithm progresses towards the center of the unknown region with more number of unknown pixels, the overall confidence of the patch drops significantly, dropping the priority value. This results into less visually acceptable inpainting. An intuitionistic fuzzy set based inpainting approach is applied to reconstruct heritage images
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