TY - GEN
T1 - Removal of Gaussian noise from stationary image using shift invariant wavelet transform
AU - Gupta, Vikas
AU - Mahle, Rajesh
AU - Shukla, Ashish
PY - 2013
Y1 - 2013
N2 - Discrete wavelet transform (DWT) has gained widespread recognition and popularity in image processing due to its ability of capturing energy of signal in a few energy transform value. As well as it has also ability to underline and represent time-varying spectral properties of many transient and other nonstationary signals. In DWT denoising is done only in detail coefficient, this offer advantage of smoothness and adaption. However DWT has a lack of shift invariance. This shift-variance is a major problem with the use of DWT for transient signal analysis and pattern recognition applications. Denoising of images with the DWT some time also give visual artifacts due to Gibbs phenomena in neighbourhood of discontinuities. In this paper, a shift-invariant analysis scheme is proposed for removing of additive Gaussian noise in stationary image. An investigation has been made on discrete wavelet transform with shift invariant in terms of PSNR and visual performance.
AB - Discrete wavelet transform (DWT) has gained widespread recognition and popularity in image processing due to its ability of capturing energy of signal in a few energy transform value. As well as it has also ability to underline and represent time-varying spectral properties of many transient and other nonstationary signals. In DWT denoising is done only in detail coefficient, this offer advantage of smoothness and adaption. However DWT has a lack of shift invariance. This shift-variance is a major problem with the use of DWT for transient signal analysis and pattern recognition applications. Denoising of images with the DWT some time also give visual artifacts due to Gibbs phenomena in neighbourhood of discontinuities. In this paper, a shift-invariant analysis scheme is proposed for removing of additive Gaussian noise in stationary image. An investigation has been made on discrete wavelet transform with shift invariant in terms of PSNR and visual performance.
UR - https://www.scopus.com/pages/publications/84887383388
UR - https://www.scopus.com/pages/publications/84887383388#tab=citedBy
U2 - 10.1109/WOCN.2013.6616223
DO - 10.1109/WOCN.2013.6616223
M3 - Conference contribution
AN - SCOPUS:84887383388
SN - 9781467359993
T3 - IFIP International Conference on Wireless and Optical Communications Networks, WOCN
BT - 2013 10th International Conference on Wireless and Optical Communications Networks, WOCN 2013
T2 - 10th IEEE and IFIP International Conference on Wireless and Optical Communications Networks, WOCN 2013
Y2 - 26 July 2013 through 28 July 2013
ER -