29 April 2016 Memory efficient and constant time 2D-recursive spatial averaging filter for embedded implementations
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Abstract
Spatial Averaging Filters (SAF) are extensively used in image processing for image smoothing and denoising. Their latest implementations have already achieved constant time computational complexity regardless of kernel size. However, all the existing O(1) algorithms require additional memory for temporary data storage. In order to minimize memory usage in embedded systems, we introduce a new two-dimensional recursive SAF. It uses previous resultant pixel values along both rows and columns to calculate the current one. It can achieve constant time computational complexity without using any additional memory usage. Experimental comparisons with previous SAF implementations shows that the proposed 2D-Recursive SAF does not require any additional memory while offering a computational time similar to the most efficient existing SAF algorithm. These features make it especially suitable for embedded systems with limited memory capacity.
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Qifeng Gan, Lama Seoud, Houssem Ben Tahar, J.M. Pierre Langlois, "Memory efficient and constant time 2D-recursive spatial averaging filter for embedded implementations", Proc. SPIE 9897, Real-Time Image and Video Processing 2016, 989705 (29 April 2016); doi: 10.1117/12.2223740; https://doi.org/10.1117/12.2223740
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