Abstract
One of the most common image artifacts is blurring. Blind methods have been developed to restore a clear image from blurred input. In this paper, we introduce a new method which optimizes previous works and adapted with medical images. Optimized non-linear anisotropic diffusion was used to reduce noise by choosing constants correctly. After de-noising, edge sharpening is done using shock filters. A novel enhanced method called Coherence-Enhancing shock filters helped us to have strong sharpened edges. To obtain a blur kernel, we used the coarse-to-fine method. In the last step, we used spatial prior before restoring the unblurred image. Experiments with images show that combining these methods may outperform previous image restoration techniques in order to obtain reliable accuracy.
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Acknowledgements
The authors appreciate those who contributed to make this research successful. This research is supported by Center for Research and Innovation (PPPI) and Faculty of Engineering, Universiti Malaysia Sabah (UMS) under the Research Grant (SBK0393-2018).
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Amini Gougeh, R., Yousefi Rezaii, T., Farzamnia, A. (2021). Medical Image Enhancement and Deblurring. In: Md Zain, Z., et al. Proceedings of the 11th National Technical Seminar on Unmanned System Technology 2019 . NUSYS 2019. Lecture Notes in Electrical Engineering, vol 666. Springer, Singapore. https://doi.org/10.1007/978-981-15-5281-6_38
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DOI: https://doi.org/10.1007/978-981-15-5281-6_38
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