Memory efficient and constant time 2D-recursive spatial averaging filter for embedded implementations

From National Research Council Canada

DOI	Resolve DOI: https://doi.org/10.1117/12.2223740
Author	Search for: Gan, Qifeng; Search for: Séoud, Lama; Search for: Ben tahar, Houssem; Search for: Langlois, J.M. Pierre
Editor	Search for: Kehtarnavaz, Nasser; Search for: Carlsohn, Matthias F.
Format	Text, Article
Conference	SPIE Photonics Europe, Sunday 3 April 2016, Brussels, Belgium
Subject	mean filtering; spatial averaging; memory efficient; recursion algorithm
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.
Publication date	2016-04-29
In	Applications of Real-Time Image Processing: 989705–.
Series	Proceedings of SPIE, no. 9897.
Language	English
Peer reviewed	Yes
NRC publication	This is a non-NRC publication "Non-NRC publications" are publications authored by NRC employees prior to their employment by NRC.
NPARC number	23000998
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Record identifier	4e9b0bf2-eae9-4d36-9d86-4ea3d85898e8
Record created	2016-11-25
Record modified	2020-03-16

Date modified:: 2025-11-13