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Proceedings Paper

Memory efficient and constant time 2D-recursive spatial averaging filter for embedded implementations
Author(s): Qifeng Gan; Lama Seoud; Houssem Ben Tahar; J.M. Pierre Langlois
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Paper 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.

Paper Details

Date Published: 29 April 2016
PDF: 7 pages
Proc. SPIE 9897, Real-Time Image and Video Processing 2016, 989705 (29 April 2016); doi: 10.1117/12.2223740
Show Author Affiliations
Qifeng Gan, DIAGNOS Inc. (Canada)
Lama Seoud, DIAGNOS Inc. (Canada)
Houssem Ben Tahar, DIAGNOS Inc. (Canada)
J.M. Pierre Langlois, Ecole Polytechnique de Montréal (Canada)


Published in SPIE Proceedings Vol. 9897:
Real-Time Image and Video Processing 2016
Nasser Kehtarnavaz; Matthias F. Carlsohn, Editor(s)

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