A Low Redundancy Wavelet Entropy Edge Detection Algorithm

Article

Tao, Yiting, Scully, Thomas, Perera, Asanka G., Lambert, Andrew and Chahl, Javaan. 2021. "A Low Redundancy Wavelet Entropy Edge Detection Algorithm." Journal of Imaging. 7 (9). https://doi.org/10.3390/jimaging7090188
Article Title

A Low Redundancy Wavelet Entropy Edge Detection Algorithm

ERA Journal ID213284
Article CategoryArticle
AuthorsTao, Yiting, Scully, Thomas, Perera, Asanka G., Lambert, Andrew and Chahl, Javaan
Journal TitleJournal of Imaging
Journal Citation7 (9)
Article Number188
Number of Pages19
Year2021
PublisherMDPI AG
Place of PublicationSwitzerland
ISSN2313-433X
Digital Object Identifier (DOI)https://doi.org/10.3390/jimaging7090188
Web Address (URL)https://www.mdpi.com/2313-433X/7/9/188
Abstract

Fast edge detection of images can be useful for many real-world applications. Edge detection is not an end application but often the first step of a computer vision application. Therefore, fast and simple edge detection techniques are important for efficient image processing. In this work, we propose a new edge detection algorithm using a combination of the wavelet transform, Shannon entropy and thresholding. The new algorithm is based on the concept that each Wavelet decomposition level has an assumed level of structure that enables the use of Shannon entropy as a measure of global image structure. The proposed algorithm is developed mathematically and compared to five popular edge detection algorithms. The results show that our solution is low redundancy, noise resilient, and well suited to real-time image processing applications.

KeywordsShannon entropy; wavelet decomposition; edge detection
Contains Sensitive ContentDoes not contain sensitive content
ANZSRC Field of Research 20204603. Computer vision and multimedia computation
Byline AffiliationsUniversity of South Australia
University of New South Wales
Defence Science and Technology Group, Australia
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