A study on non-local image denoising method based on noise estimation

노이즈 수준 추정에 기반한 비지역적 영상 디노이징 방법 연구

  • Lim, Jae Sung (DTaQ(Defence agency for Technology and Quality))
  • 임재성 (국방기술품질원 유도전자센터)
  • Received : 2017.01.20
  • Accepted : 2017.05.12
  • Published : 2017.05.31


This paper proposes a novel denoising method based on non-local(NL) means. The NL-means algorithm is effective for removing an additive Gaussian noise, but the denoising parameter should be controlled depending on the noise level for proper noise elimination. Therefore, the proposed method optimizes the denoising parameter according to the noise levels. The proposed method consists of two processes: off-line and on-line. In the off-line process, the relations between the noise level and the denoising parameter of the NL-means filter are analyzed. For a given noise level, the various denoising parameters are applied to the NL-means algorithm, and then the qualities of resulting images are quantified using a structural similarity index(SSIM). The parameter with the highest SSIM is chosen as the optimal denoising parameter for the given noise level. In the on-line process, we estimate the noise level for a given noisy image and select the optimal denoising parameter according to the estimated noise level. Finally, NL-means filtering is performed using the selected denoising parameter. As shown in the experimental results, the proposed method accurately estimated the noise level and effectively eliminated noise for various noise levels. The accuracy of noise estimation is 90.0% and the highest Peak Signal-to-noise ratio(PSNR), SSIM value.


Additive white Gaussian noise(AWGN);noise level;non-local means(NL-means) filter;noise estimation;denoising parameter(h parameter)


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