Affiliation: School of Computer Science and Engineering (SCSE), UITS, Dhaka, Bangladesh.
The wavelet transform converts a signal in one domain into another for better understanding of the structure and features of any given signal. Recently, performance of various denoising methods has been analyzed and the result shows that Fourth order moment based denoising provides better performance, in the same study the proposed modified Fourth order moment denoising provides better Bit Error Rate (BER) performance than previous work. Wiener filtering is an excellent method to estimate a noisy signal. In this work, the modified Fourth order moment based denoising technique is used in Wavelet domain (WD) Wiener filtering algorithm to estimate less noisy Wavelet coefficient for denoising purpose. The modified Fourth order moment reduces noise by allowing wavelet coefficients having noise below a certain threshold level. Computer simulation is performed to investigate the performance of the proposed technique. The simulation result shows that the joint use of WD-Wiener filter in modified Fourth order moment based denoising provides better BER performance than that of modified Fourth order moment based denoising. Finally, Wiener filter was also applied to detect noise free image through the same noisy fading channel.