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• W2972324374 abstract "The recent increase in the extensive use of digital imaging technologies has brought with it a simultaneous demand for higher-resolution images. We develop a novel edge-informed approach to single image super-resolution (SISR). The SISR problem is reformulated as an image inpainting task. We use a two-stage inpainting model as a baseline for super-resolution and show its effectiveness for different scale factors (x2, x4, x8) compared to basic interpolation schemes. This model is trained using a joint optimization of image contents (texture and color) and structures (edges). Quantitative and qualitative comparisons are included and the proposed model is compared with current state-of-the-art techniques. We show that our method of decoupling structure and texture reconstruction improves the quality of the final reconstructed high-resolution image. Code and models available at: this https URL" @default.
• W2972324374 created "2019-09-19" @default.
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• W2972324374 date "2019-09-11" @default.
• W2972324374 modified "2023-09-27" @default.
• W2972324374 title "Edge-Informed Single Image Super-Resolution" @default.
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