Improvement of CNN Denoising Performance Using Noise Control of Input Image and Application to Parallelized Image Denoising

In noise reduction, the lower the amount of noise, the lower the image degradation associated with the noise reduction. Using this property, we propose a new denoising scheme that can improve denoising performance using trained CNN. Noise suppressed image by low-pass filter is inputted to denoising CNN and then output image is enhanced by high-pass filter. Experimental results show that noise suppression of the input image improves both image structure preservation and noise processing performance. The proposed method was applied to a parallel blind image denoising method. As a results, further improvement in performance was shown.