关键词: 图像去噪, 离散余弦变换, 组群, PC分量, Kaiser窗口

Abstract: This paper proposed an image denoising method using transform-domain sparse representation with the characteristic that fewer Discrete Cosine Transformation (DCT) nonzero coefficients exist in image smoothing-domain. This method overcame the shortcoming of traditional denoising method, i.e. losing information of edge and texture. Firstly, similar image block was grouped by computing l2 norm; secondly, according to transform-domain coefficient sparsity, denoising was performed by threshold. To improve it, Principal Component Analysis (PCA) was used on these groups, processing groups with PC components. Lastly, the image with processed groups was reconstructed using Kaiser windows method. Compared to traditional method, this method preserves image edge and texture information, so that the noise could be preferably removed and the effect of image visual could be improved.

Key words: image denoising, Discrete Cosine Transform (DCT), grouping, PC component, Kaiser window