Abstract
Digital imaging is used in variety of applications. Together with the improvements in artificial intelligence and its sub-fields, improving computer vision methods to address inter- and multi-disciplinary problems is possible. Especially in medical applications, there are significant improvements related to imaging in the last decades. Digital image interpolation is a key operation in digital image processing where there are no sufficient samples during the acquisition process. Using the available samples in hand, digital interpolation techniques are predicting the missing samples. The paper addresses the problem of digital image interpolation and proposes a novel algorithm using multiplicative calculus. The main contribution of the paper is the application of multiplicative Lagrange interpolation to accomplish image interpolation task. The proposed method is tested on several datasets, and the results are comparable to the state-of-the-art methods. The paper presents encouraging results to the literature, and the proposed method is open for further improvements.
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G.O., K.Y. and A.O. were involved in conceptualization, investigation, resources, data curation, visualization, project administration, and validation; G.O. and K.Y. contributed to methodology; G.O. was involved in formal analysis, software, writing—review and editing, writing—original draft preparation. K.Y. and A.O. contributed to supervision.
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Othman, G.M., Yurtkan, K. & Özyapıcı, A. Improved digital image interpolation technique based on multiplicative calculus and Lagrange interpolation. SIViP 17, 3953–3961 (2023). https://doi.org/10.1007/s11760-023-02625-9
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DOI: https://doi.org/10.1007/s11760-023-02625-9