The recently introduced non-local means (NLM) image denoising technique broke the traditional
paradigm according to which image pixels are processed by their surroundings. Non-local means technique
was demonstrated to outperform state-of-the art denoising techniques when applied to images in the visible.
This technique is even more powerful when applied to low contrast images, which makes it tractable for
denoising infrared (IR) images. In this work we investigate the performance of NLM applied to infrared
images. We also present a new technique designed to speed-up the NLM filtering process. The main
drawback of the NLM is the large computational time required by the process of searching similar patches.
Several techniques were developed during the last years to reduce the computational burden. Here we present
a new techniques designed to reduce computational cost and sustain optimal filtering results of NLM
technique. We show that the new technique, which we call Multi-Resolution Search NLM (MRS-NLM),
reduces significantly the computational cost of the filtering process and we present a study of its performance
on IR images.
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.