Image Denoising Algorithm Based on Neighbouring Thresholding Classification in Wavelet Domain

This paper proposes a new image denoising method which exploits spatial correlation among image wavelet coefficients and classification technique. By extending the neighbouring threshold of wavelet coefficients for 1D signal to 2D image case, each coefficient in a subband is classified as "large" or "small" category, according to its corresponding neighbouring threshold. Different strategies are implemented to the classified coefficients. Simulation results show that although very simple, the performance of the proposed method can be competitive to the two excellent state of the art denoising algorithms with spatial adaptivity