A new method for image de-noising on the basis of Chen-Mobius transform

The purpose of this paper is to study a new method of de-noising images corrupted with additive white Gaussian noise. Based on the Chen-Mobius transform, the idea of modulation and demodulation in Chen-Mobius communication system is applied in the image de-noising. The evaluation results of the Chen-Mobius transform of some often-used waveforms are applied in the anti-noise of image. For image de-noising, the data is modulated on a modulation wave for some period and recorded by a certain means, then the data can be carried everywhere. To make such a processing, the Chen-Mobius inverse transformed functions act as the “modulation” waveforms and the receiving end is coherently “demodulated” by the often-used digital waveforms. Simulation results are discussed in some detail. It shows that the new application has excellent performances that the digital image signals can be restored from intense Gaussian noise. Here, to prove the performance of the proposed method, the results are compared with other existent methods or algorithms such as hard and soft threshold based on wavelet. The simulation results on several testing images indicate that the proposed method outperforms the other methods in peak signal to noise ratio and keeps better visual in edges information reservation as well. The results also suggest that Chen-Mobius transform can achieve a better performance than the wavelet transform in image de-noising.