Title
A q-Extension of Sigmoid Functions and the Application for Enhancement of Ultrasound Images
Abstract
This paper proposes the q-sigmoid functions, which are variations of the sigmoid expressions and an analysis of their application to the process of enhancing regions of interest in digital images. These new functions are based on the non-extensive Tsallis statistics, arising in the field of statistical mechanics through the use of q-exponential functions. The potential of q-sigmoids for image processing is demonstrated in tasks of region enhancement in ultrasound images which are highly affected by speckle noise. Before demonstrating the results in real images, we study the asymptotic behavior of these functions and the effect of the obtained expressions when processing synthetic images. In both experiments, the q-sigmoids overcame the original sigmoid functions, as well as two other well-known methods for the enhancement of regions of interest: slicing and histogram equalization. These results show that q-sigmoids can be used as a preprocessing step in pipelines including segmentation as demonstrated for the Otsu algorithm and deep learning approaches for further feature extractions and analyses.
Year
DOI
Venue
2019
10.3390/e21040430
ENTROPY
Keywords
DocType
Volume
contrast enhancement,sigmoid,Tsallis statistics,q-exponential,q-sigmoid,q-Gaussian,ultra-sound images
Journal
21
Issue
ISSN
Citations 
4
1099-4300
0
PageRank 
References 
Authors
0.34
0
5