Denoising Iris Image Using a Novel Wavelet Based Threshold

The efficiency of an iris authentication system depends on the quality of the iris image. Denoising of the iris image is indispensable to get a noise free image. In this paper, a novel method is proposed to remove Gaussian noise present in the iris image using Undecimated wavelet, a threshold based on Golden Ratio and weighted median. First, decompose the input image using Stationary Wavelet Transform (SWT) and apply the modified Visushrink to the wavelet coefficients using hard and soft thresholding. Then apply inverse SWT to get the noise free image. Different kinds of wavelet filters such as db1, db2, sym2, sym4, coif2 and coif4 for different noise levels are performed. The filter db1 is outperformed. In this research, experiments have been conducted on the iris database CASIA. The Peak Signal-to-Noise Ratio (PSNR), Signal-to-Noise Ratio (SNR), Root Mean Square Error (RMSE) and Mean Square Error (MSE) have been computed and compared.