TY - JFULL AU - Iman Elyasi and Sadegh Zarmehi PY - 2009/9/ TI - Elimination Noise by Adaptive Wavelet Threshold T2 - International Journal of Electrical and Computer Engineering SP - 1540 EP - 1545 VL - 3 SN - 1307-6892 UR - https://publications.waset.org/pdf/8882 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 32, 2009 N2 - Due to some reasons, observed images are degraded which are mainly caused by noise. Recently image denoising using the wavelet transform has been attracting much attention. Waveletbased approach provides a particularly useful method for image denoising when the preservation of edges in the scene is of importance because the local adaptivity is based explicitly on the values of the wavelet detail coefficients. In this paper, we propose several methods of noise removal from degraded images with Gaussian noise by using adaptive wavelet threshold (Bayes Shrink, Modified Bayes Shrink and Normal Shrink). The proposed thresholds are simple and adaptive to each subband because the parameters required for estimating the threshold depend on subband data. Experimental results show that the proposed thresholds remove noise significantly and preserve the edges in the scene. ER -