An adaptive image in painting method based on the modified Mumford-Shah model and multiscale parameter estimation
Автор: Thanh Dang Ngoc Hoang, Surya Prasath V. B., Son Nguyen Van, Hieu Le Minh
Журнал: Компьютерная оптика @computer-optics
Рубрика: Обработка изображений, распознавание образов
Статья в выпуске: 2 т.43, 2019 года.
Бесплатный доступ
Image inpainting is a process of filling missing and damaged parts of image. By using the Mumford-Shah image model, the image inpainting can be formulated as a constrained optimization problem. The Mumford-Shah model is a famous and effective model to solve the image inpainting problem. In this paper, we propose an adaptive image inpainting method based on multiscale parameter estimation for the modified Mumford-Shah model. In the experiments, we will handle the comparison with other similar inpainting methods to prove that the combination of classic model such the modified Mumford-Shah model and the multiscale parameter estimation is an effective method to solve the inpainting problem.
Image inpainting, mumford-shah model, modified mumford-shah model, regularization, euler-lagrange equation, inverse gradient, multiscale
Короткий адрес: https://sciup.org/140243286
IDR: 140243286
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