K-SVD Based Image Denoising Method Using Image Residual Information in Different Frequency Bands

摘要

The common image denoising methods only consider how to restore well image information from noise images, but neglect the effects of residual information between restored images and given images. To enhance denoised image's quality, a new image denoising method considering residual information in different frequency bands is discussed in this paper. In this method, an original image is divided into high and low frequency sub-band images by the contourlet transform algorithm. And each sub-band image is first denoised by the K-singular value decomposition (K-SVD) denoising model, thus each residual sub-band image is correspondingly obtained. Further, each residual image is again denoised by K-SVD denoising model. Finally, for each sub-band image denoised and its residual image, the inverse transform of contourlet transform algorithm is used to restore the original image. Compared our method proposed here with common denoising methods of wavelet, contourlet, K-SVD, experimental results show that our method fusing residual information in different frequency bands behaves better denoising effect.