VISUAL IMAGE PROCESSING LABORATORY
A research project on computational vision science.

Funded by Generalitat Valenciana under grant AICO-2020-136 (VIPLab) and CIAICO/2022/051 (IMaLeVICS) 

Image Noise Reduction by bootstrap resampling

Oct 17, 2022 | Publications

Bootstrapping-Based Fuzzy Numbers

Reza Ghasemi, Samuel Morillas, Ahmad Nezakati and Mohammadreza Rabiei. Image Noise Reduction by Means of Bootstrapping-Based Fuzzy Numbers. Appl. Sci. 2022, 12, 9445.

As you know, nonlinear methods significantly reduce image noise and are widely used today. One of type of nonlinear performance is achieve through the use of of fuzzy logic.

In our work «Image Noise Reduction by Means of Bootstrapping-Based Fuzzy Numbers«, In our work, «Image Noise Reduction by Means of Bootstrapping-Based Fuzzy Numbers«, we present a fuzzy filter with enhanced performance thanks to using bootstrap resampling method to reduce the effect of outliers.

The concept of the strong law of large numbers for the bootstrap mean in fuzzy metric space helps us to use the resampling method.

If you want to test the methods’ performance, download the code here: