Noise reduction based on Double Density Discrete Wavelet Transform

Author

Vimala, C. ; Priya, P. Aruna

Author_Institution

Dept. of TCE, SRM Univ., Kattankulathur, India

fYear

2014

fDate

9-9 Oct. 2014

Firstpage

15

Lastpage

18

Abstract

The wavelet transform is a well-known tool that can be used for many signal processing applications. This paper investigates the success of Double Density Discrete Wavelet Transform (DDDWT) to denoise the signals and images. The performance analysis of one dimensional signal and two dimensional images are compared with discrete wavelet transform (DWT). The Double Density DWT has an one scaling function and two wavelet functions. With these two wavelets gives a closer spacing between adjacent wavelets within the same scale. It is found that with same level of processing, the double density DWT (DDDWT) performs better than DWT.

Keywords

discrete wavelet transforms; image denoising; DDDWT; adjacent wavelets; double density discrete wavelet transform; image denoising; noise reduction; scaling function; signal denoising; signal processing applications; wavelet functions; Discrete wavelet transforms; Filter banks; Noise measurement; Noise reduction; PSNR; DDDWT; DWT; Image; denoising; signal;

fLanguage

English

Publisher

ieee

Conference_Titel

Smart Structures and Systems (ICSSS), 2014 International Conference on

Conference_Location

Chennai

Print_ISBN

978-1-4799-6506-9

Type

conf

DOI

10.1109/ICSSS.2014.7006177

Filename

7006177