Infrared image denoising by nonlocal means filtering

Barak Dee-Noor; Adrian Stern; Yitzhak Yitzhaky; Natan Kopeika

doi:10.1117/12.919979

7 May 2012 Infrared image denoising by nonlocal means filtering

Barak Dee-Noor, Adrian Stern, Yitzhak Yitzhaky, Natan Kopeika

Proceedings Volume 8399, Visual Information Processing XXI; 83990K (2012) https://doi.org/10.1117/12.919979
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

Abstract

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.

Citation Download Citation

Barak Dee-Noor, Adrian Stern, Yitzhak Yitzhaky, and Natan Kopeika "Infrared image denoising by nonlocal means filtering", Proc. SPIE 8399, Visual Information Processing XXI, 83990K (7 May 2012); https://doi.org/10.1117/12.919979

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