• Journal of IKEEE
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• v.24 no.2
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• pp.507-513
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• 2020

The median filter that is used in various fields requiring image processing converts to a median value of pixels belonging to a radius r for all pixels in the image of n×m size. For 8-bit depth images, an O(nm) time algorithm exists but for over 16-bit depth images, there is an O(nmlog²r) time algorithm of Gil and Werman. In this paper, we propose an efficient median filter algorithm that works for more than 16-bit depth images. The time complexity of our algorithm is the same as that of Gil and Werman, but theoretical analysis and experimental results show that ours is efficient than above two times.

• Journal of IKEEE
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• v.26 no.2
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• pp.240-248
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• 2022

Floating-point images that express pixel information as real numbers are used in HDR images. There have been various researches on efficient median filter algorithms, but most of them are applicable to 8-bit depth images and there are only a few number of algorithms applicable to floating-point images, including Gil and Werman's algorithm. In this paper, we propose a median filter algorithm that works efficiently on floating-point images by improving Kim's algorithm, which improved Gil and Werman's algorithm. Experimental results show that the execution time is improved by about 10% compared to the Kim's algorithm by reducing the redundant work for the repetitively used binary search tree and applying the inverted index.