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Noise Cancellation by Combining the Discrete Wavelet Transform With the Wiener Filter

In this study by using noise-free signal estimation the reduction of noise in the image is being proposed. The dyadic stationary wavelet transform is used for both the wiener filter and in estimating the noise free signal. Finding a suitable filter bank and choosing other parameters of the wiener filter with respect to obtained signalto-noise ratio (SNR) is our goal. Testing was being performed on the standard images corrupted with the noise. The artificial interference was created from the generated white Gaussian noise, whose power spectrum was modified according to a model of the power spectrum of the image. The adaptive setting parameters of the filtering according to the level of interference in the input signal are being used to improve the filtering performance. The average SNR of the whole test database is increased by about 10.6 dB. The better results can be provided by using the provided algorithm than the classic wavelet wiener filter