A New Denoising Algorithm Based on Spherical Coordinates for IOT

Author

Zhang, De-gan ; Dong, Dan-chao ; Zhao, Chen-peng ; Zhu, Yan-nan ; Kang, Xue-jing

Author_Institution

Tianjin Key Lab. of Intell. Comput. & Novel Software Technol., Tianjin Univ. of Technol., Tianjin, China

fYear

2012

fDate

4-6 June 2012

Firstpage

781

Lastpage

784

Abstract

This paper proved a new adaptive threshold in spherical coordinate system based on Besov space norm theory for application of the internet of things (IOT). It presented a new adaptive curve shrinkage function to overcome the limitation of translational functions. The new function could reach and exceed the true value and enhance the image edge. According to the image statistical characteristics in the spherical coordinates, to process the radial component with the new thresholds and new shrinkage function. The simulation experiments evaluated the new algorithm from the peak signal noise ratio, mean square error and running time.

Keywords

Internet; image denoising; image enhancement; mean square error methods; shrinkage; Besov space norm theory; IOT; Internet of things; adaptive curve shrinkage function; image denoising algorithm; image edge enhancement; image statistical characteristic; mean square error; peak signal noise ratio; shrinkage function; spherical coordinate system; translational function; Image denoising; Image edge detection; Image reconstruction; Noise; Noise reduction; Wavelet coefficients; IOT; denoising; image; spherical coordinates; wavelet;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer, Consumer and Control (IS3C), 2012 International Symposium on

Conference_Location

Taichung

Print_ISBN

978-1-4673-0767-3

Type

conf

DOI

10.1109/IS3C.2012.201

Filename

6228424