Complex Wavelet Transform Based Denoising and Resolution Enhancement of Noisy Images

A dual tree complex wavelet transform (DT -CWT)based directional interpolation scheme for denoising of noisy images is proposed . The problems of denoising and interpolation are modeled as to estimate the noiseless and missing samples under the same framework of optimal estimation. Initially, DT -CWT is used to decompose an input low-resolution noisy wage irito low and high frequency subbands. The highfrequency subband images are interpolated by linear minimum mean square estimation (LMMSE) based interpolation, which preserves the edges of the interpolated images. For each noisy LR image sample, we compute multiple estimates of it along different directions and then fuse those directional estimates for a more accurate denoised LR image. The estimation parameters calculated in the denoising processing can be readily used to interpolate the missing samples. The inverse DT-CWT is applied on the denoised input and interpolated high frequency subband images to obtain the high resolution image. Compared with the conventional schemes that perform denoising and interpolation in. tandem, the proposed DT -CWT based noisy image interpolation method can reduce many noisecaused interpolation artifacts and preserve well the image edge structures. The visual and quantitative results show that the proposed technique outperforms many of the existing denoising and interpolation methods.