Image inpainting by anisotropic gradient estimation

A. Zelensky; N. Gapon; M. Zhdanova; V. Voronin; Y. Ilukhin; I. Khamidullin

doi:10.1117/12.3038592

22 November 2024 Image inpainting by anisotropic gradient estimation

A. Zelensky, N. Gapon, M. Zhdanova, V. Voronin, Y. Ilukhin, I. Khamidullin

Proceedings Volume 13239, Optoelectronic Imaging and Multimedia Technology XI; 132391X (2024) https://doi.org/10.1117/12.3038592
Event: SPIE/COS Photonics Asia, 2024, Nantong, Jiangsu, China

Conference Poster

Abstract

Automatic restoration of damaged or missing pixels is a key problem in image reconstruction for various applications such as retouching, image restoration, image coding, and computer vision. This paper presents a novel approach for reconstructing texture and edge regions, focusing on achieving fine detail in image completion. The proposed method employs spatial reconstruction based on a geometric model, incorporating contour and exemplar-based texture analysis. We propose a technique for restoring object boundaries in images by constructing composite curves using cubic splines and anisotropic gradients. The shape-dependent gradients utilize the distinct forms in the structural pattern to encode both textural and contour information. Additionally, we search for similar patches, fuse them, and apply a deep neural network. We evaluate our model end-to-end on publicly available datasets, demonstrating that it outperforms current state-of-the-art techniques both quantitatively and qualitatively.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

A. Zelensky, N. Gapon, M. Zhdanova, V. Voronin, Y. Ilukhin, and I. Khamidullin "Image inpainting by anisotropic gradient estimation", Proc. SPIE 13239, Optoelectronic Imaging and Multimedia Technology XI, 132391X (22 November 2024); https://doi.org/10.1117/12.3038592

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