Абстрактный

Image Denoising Using Complex Framelets

N. Gayathri, A. Hazarathaiah.

In certain signal processing applications, like denoising, over complete transforms can offer a better tradeoff between performance and complexity, compared to critically sampled transforms. This paper introduces the double-density (DD) dual-tree discrete wavelet transform (DWT), which is a DWT that combines the double-density DWT and the dualtree DWT, has its own characteristics and it has own advantages. The transform corresponds to a dyadic wavelet tight frames based on two scaling functions and four distinct wavelets. Experiments are conducted to not only demonstrate that the proposed method is more suitable than conventional methods, but also show shows that the proposed image denoising approach outperforms the conventional approaches.