The research of wavelet adaptive threshold gray scale image denoising

The characteristics of two traditional wavelet compromise methods, referred to as the soft-thresholding method and the hard thresholding method, were analyzed in the wavelet domain. A new compromise thresholding method that improves peak-signal-to-noise ratio (PSNR) of denoising is presented, based on the standard compromise threshold method, yet more flexible and easier to treat mathematically. Compared with traditional wavelet compromise methods, the new approach avoids the discontinuity of the hard-threshold method and also decreases the fixed bias between the estimated wavelet coefficients and the decomposed wavelet coefficients of the soft-threshold method. Simulation results show that the improved method is better at the adaptability, at the same time increase the correlation judgment process, improve image details loss problem.