Bilateral filtering provides a scheme for noniterative edge-preserving smoothing, but the results could be strongly affected by the presence of outliers. In this paper we develop a robust bilateral filter for color images, and in order to achieve this we propose to improve the bilateral filtering technique [13] by using Ordered Weighted Averaging operators. We adopt a fuzzy logic based approach: if the filtering is considered as a weighted averaging, then each filter is associated with a fuzzy set and the membership values of these fuzzy sets represent the weights. In this context, the bilateral filter is a conjunction of two fuzzy sets in the case of grayscale images: one in the spatial domain and one in a photometric domain. Applied to color images, we propose to extend the conjunction to three fuzzy sets: one in the spatial domain, one in the brightness domain and one in the chromatic domain. Taking into account the robustness of rank filters, we propose to define an OWA filter in order to obtain robust adaptive filters in brightness and chromaticity. The robustness and performance of the filter is illustrated with several experiments, revealing its ability to remove different types of noise in the presence of outliers, while preserving edges. The noise types considered are impulse noise and a combination of Gaussian noise with "salt and pepper" noise types.
Digitized methodologies in the recent era contribute to various fields of automation that used to hold different interests and meanings of human life. Buildings with historical significance, cultural values, and beliefs are becoming an interdisciplinary field of interest, engaging more computer scientists nowadays. Such structures need more attention towards reconstructing their values using a flavor of computerized tools instead of brickwork directly. Due to the wear of time, the tiles and engravings of most of the historical monuments are on the verge of ruin, endangering significant historical values. In this survey, we rebuild the values by delving deep into the device and methodologies by providing a comprehensive understanding of emerging fields and some experimental decisions. We discuss heritage restoration from some essential papers on 3D reconstruction, image inpainting, IoT-based methods, genetic algorithms, and image processing. The survey explains Machine Learning, Deep Learning, and Computer Vision-based methods for various restoration tasks in the related field. We divide this into certain parts contributing to different fields that restore cultural heritage. Moreover, we infer that the techniques will be faster, cheaper, and more beneficial to the context of image reconstruction in the near future.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.