Image denoising using regularized Butterworth wavelet frames

We present an efficient algorithm for image restoration from highly noised originals. The algorithm is based on diverse library of tight and semi-tight wavelet frames. Unlike majority of current denoising methods, which threshold the transform coefficients, our algorithm performs direct and inverse multiscale transforms using properly modified frame filters. No thresholding is applied. The processing is linear. The algorithm is fast and can be implemented in real time. It depends on one numerical parameter, which is estimated from the noise level.