Abstract: According to the disadvantages of sparse coding shrinkage and Contourlet transform，a new image denoising algorithm is introduced.For that an infrared image is corrupted by additive noise with unknown variance，this algorithm is very effective.Experimental results show that this algorithm improves the SNR value，reduces the MSE value and obtains a better quality of image restoration comparing with other methods such as traditional denoising methods，sparse coding shrinkage and methods based on Contourlet transform.

摘要： 针对稀疏收缩编码法和Contourlet变换的不足，提出了一种新的图像去噪算法。算法可以很好地解决含有加性未知噪声方差的红外图像去噪问题。实验表明，与传统方法、稀疏编码收缩法和Contourlet域降噪方法相比，该算法进一步提高了SNR值，降低了MSE值，获得了更好的图像恢复质量。