As traditional denoising algorithm can’t deal with the infrared image with noise signal well,an infrared image denoising algorithm of neighborhood coefficient correlation and inter-scale dependency based on WBC transform is proposed by analyzing infrared image’s correlation of the neighborhood coefficient after the WBC transform. Firstly,the generalized CB morphology is applied to neighborhood coefficient denoising. Then,infrared images are denoised combining with the self-adaptive threshold based on inter-scale dependency. The results show the proposed algorithm can get higher SNR compared with Bayes estimation denoising method,WBC inter-scale hard-threshold denoising method and WBC inter-scale adaptive threshold denoising method. Its SSIM is also closer to 1.