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Computationally efficient image deblurring using low rank image approximation and its GPU implementation

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Abstract

This paper presents a computationally efficient technique for reduction of blur caused by handshakes in images captured by mobile devices. This technique uses a short-exposure or a low-exposure image that is captured at the same time a normal or auto-exposure image is captured. The short-exposure image is enhanced by utilizing low rank image approximation of the auto-exposure image without requiring any user specified parameters. Based on the three quantitative measures of image quality, it is shown that this technique outperforms similar techniques used for image deblurring while it also offers computational efficiency. A GPU implementation of this technique is also reported.

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Authors and Affiliations

  1. Richardson, TX, USA

    Chih-Hsiang Chang & Nasser Kehtarnavaz

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  1. Chih-Hsiang Chang
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  2. Nasser Kehtarnavaz
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Correspondence to Chih-Hsiang Chang.

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Chang, CH., Kehtarnavaz, N. Computationally efficient image deblurring using low rank image approximation and its GPU implementation. J Real-Time Image Proc 12, 567–573 (2016). https://doi.org/10.1007/s11554-015-0539-x

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  • DOI: https://doi.org/10.1007/s11554-015-0539-x

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