Traditional median filtering algorithm is mainly designed for stationary noise density, which realizes the image smooth but leads to edge fuzzy. The noise density of Electron Multiplying CCD (EMCCD) image varies with the gain. In this paper, a new noise detection and fuzzy adaptive median filter (NDFAMF) is proposed to overcome such drawbacks. First, the noise pixels in the center of the filter window were identified. Secondly, the thresholds were introduced for the detected “noise points”. Based on the thresholds and median of the filtering window, the fuzzy membership function of noise points was put forward, using the fuzzy membership function to filter the noise points. Finally, according to the density of noise in the filtering window the filtering window can change the size adaptive. Simulation and experimental results show that the new algorithm is able to remove noise pixels effectively and protect the details well in the image. The performance is better than the other median filters under the condition of low noise density and relatively stable under the condition of high noise density.
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.