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Fusion of Deep and Non-Deep Methods for Fast Super-Resolution of Satellite Images

Kumar Nayak, G and Jain, S and Venkatesh Babu, R and Chakraborty, A (2020) Fusion of Deep and Non-Deep Methods for Fast Super-Resolution of Satellite Images. In: 6th IEEE International Conference on Multimedia Big Data, BigMM 2020, 24 - 26 September 2020, New Delhi, pp. 267-271.

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Official URL: https://doi.org/10.1109/BigMM50055.2020.00046


In the emerging commercial space industry there is a drastic increase in access to low cost satellite imagery. The price for satellite images depends on the sensor quality and revisit rate. This work proposes to bridge the gap between image quality and the price by improving the image quality via super-resolution (SR). Recently, a number of deep SR techniques have been proposed to enhance satellite images. However, none of these methods utilize the region-level context information, giving equal importance to each region in the image. This, along with the fact that most state-of-the-art SR methods are complex and cumbersome deep models, the time taken to process very large satellite images can be impractically high. We, propose to handle this challenge by designing an SR framework that analyzes the regional information content on each patch of the low-resolution image and judiciously chooses to use more computationally complex deep models to super-resolve more structure-rich regions on the image, while using less resource-intensive non-deep methods on non-salient regions. Through extensive experiments on a large satellite image, we show substantial decrease in inference time while achieving similar performance to that of existing deep SR methods over several evaluation measures like PSNR, MSE and SSIM. © 2020 IEEE.

Item Type: Conference Paper
Publication: Proceedings - 2020 IEEE 6th International Conference on Multimedia Big Data, BigMM 2020
Publisher: Institute of Electrical and Electronics Engineers Inc.
Additional Information: The copyright for this article belongs to the Author(s).
Keywords: Aerospace industry; Big data; Costs; Image quality; Optical resolving power; Satellite imagery, Context information; Evaluation measures; Low resolution images; Regional information; Salient regions; Satellite images; State of the art; Super resolution, Image enhancement
Department/Centre: Division of Interdisciplinary Sciences > Computational and Data Sciences
Date Deposited: 13 Jan 2023 04:50
Last Modified: 13 Jan 2023 04:50
URI: https://eprints.iisc.ac.in/id/eprint/79080

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