Moving average algorithms for diamond, hexagon, and general polygonal shaped window operations

Authors:
Changming Sun
Affiliations:
CSIRO Mathematical and Information Sciences, Locked Bag 17, North Ryde, NSW 1670, Australia
Venue:
Pattern Recognition Letters
Year:
2006

Citing 11
Cited 1

Low-level image processing by max–min filters

Signal Processing
A fast algorithm for local minimum and maximum filters on rectangular and octagonal kernels

Pattern Recognition Letters
Recursive Implementation of Erosions and Dilations Along Discrete Lines at Arbitrary Angles

IEEE Transactions on Pattern Analysis and Machine Intelligence
Periodic lines: Definition, cascades, and application to granulometries

Pattern Recognition Letters
Fast computation of morphological operations with arbitrary structuring elements

Pattern Recognition Letters
Optimal cache usage for separable image processing algorithms on general purpose workstations

Signal Processing
Fast computation of moving average and related filters in octagonal windows

Pattern Recognition Letters
Directional Morphological Filtering

IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast algorithm for local statistics calculation for N-dimensional images

Real-Time Imaging
Fast Stereo Matching Using Rectangular Subregioning and 3D Maximum-Surface Techniques

International Journal of Computer Vision
Algorithm for computer control of a digital plotter

IBM Systems Journal

Image hiding based on circular moiré fringes

WSEAS Transactions on Mathematics

Quantified Score

Hi-index	0.10

Visualization

Abstract

This paper presents fast moving window algorithms for calculating local statistics in a diamond, hexagon, and general polygonal shaped windows of an image which is important for real-time applications. The algorithms for a diamond shaped window requires only seven or eight additions and subtractions per pixel. A fast sparse algorithm only needs four additions and subtractions for a sparse diamond shaped window. A number of other shapes of diamond windows such as skewed or parallelogram shaped diamond, long diamond, and lozenged diamond shaped, are also investigated. Similar algorithms are also developed for hexagon shaped windows. The computation for a hexagon window only needs eight additions and subtractions for each pixel. Fast algorithms for general polygonal shaped windows are also developed. The computation cost of all these algorithms is independent of the window size. A variety of synthetic and real images have been tested.