Noise level estimation is a long-standing problem in image processing. The challenge arises from the estimation being easily affected by texture information. We propose an innovative noise level estimation method via the kurtosis test, which is a normalized fourth-order moment. The proposed method consists of two stages: the first one is to determine the image patches with normality using the kurtosis test; the noise level is then estimated from these selected normal patches in the second stage, in which the average of the standard deviations is used as the final estimation. Experimental results show that the proposed method outperforms the state-of-the-art estimation techniques in terms of noise level estimation and guided denoising.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.