Image Restoration Using Thresholding Techniques on Wavelet Coefficients
Rubeena Vohra, Akash Tayal · 2011
Image restoration from corrupted image is a classical problem in the field of image processing. Additive random noise can easily be removed using simple threshold methods with linear and nonlinear filtering techniques. De-noising of natural images corrupted by Gaussian noise using wavelet techniques is very effective because of its ability to capture the energy of a signal in few energy transform values. The wavelet de-noising scheme thresholds the wavelet coefficients arising from the standard discrete wavelet transform. In this paper, it is proposed to investigate the suitability of different wavelet bases and the decomposition levels on the performance of image de-noising algorithms in terms of peak signal-to- noise ratio.