Overview of image noise reduction based on non-local mean algorithm

18Citations
Citations of this article
16Readers
Mendeley users who have this article in their library.

Abstract

The system introduces the extensive application and development process of image denoising based on non-local mean. The principle and specific theoretical model of the non-local mean algorithm are described. The process of improving the non-local mean algorithm after being proposed and how to improve it is elaborated and the shortcomings of the algorithm are pointed out. The noise reduction algorithm is experimentally described in detail from the aspects of peak signal-to-noise ratio, mean square error and structural similarity under different noise environment conditions.

Cite

CITATION STYLE

APA

Liu, B., & Liu, J. (2018). Overview of image noise reduction based on non-local mean algorithm. In MATEC Web of Conferences (Vol. 232). EDP Sciences. https://doi.org/10.1051/matecconf/201823203029

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free