γ Radiation Image Denoising Based on Speckle Splitting

Abstract

Abstract The images captured with CMOS sensor in γ radiation scene mainly affected by single-shot noise, induced noise and ionized air glow noise. In this paper, we propose a two-stage image denoising method based on speckle splitting to improve the clarity of the image originated from the γ radiation scene. Concretely, we first losslessly split the noisy image into multiple sub-images by dilated down-sampling, making the speckle noise in the original image decomposed into isolated point noise in the sub-images. Secondly, the median filtering is utilized to remove salient noise in sub-images. Lastly, aiming at the problem of incomplete denoising due to subtle differences between non-salient noises and background pixels. The gradient-guided NLM filtering in YUV color space is presented for second-stage denois-ing. Extensive experiments are carried out on the images captured from Co60 γ radiation scene. Compared with the original image, our method improves the PSNR by 8.17dB and SSIM by 0.32. Experimental 1 Springer Nature 2021 L A T E X template 2 γ Radiation Image Denoising Based on Speckle Splitting results demonstrate that the proposed method enjoys the state-of-the-art performance in improving the clarity of γ radiation image.