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+---
+title: SNRstar – Covariance-based SNR measurement
+categories: [Analysis]
+doi: 10.6009/jjrt.2022-1154
+---
+
+## SNRstar – Covariance-based SNR measurement
+
+Author: Motohiro TABUCHI
+
+SNRstar is an ImageJ macro that estimates signal variance and noise variance using covariance between two repeated images acquired under identical imaging conditions.  
+It provides an unbiased and statistically optimal estimation of SNR.
+
+### Features
+
+- Covariance-based signal variance estimation
+- Noise variance estimation from difference of images
+- Outputs SNR* [dB], ROI size, signal variance, and noise variance
+- Simple workflow using ImageJ ROI tools
+
+### Requirements
+
+- ImageJ 1.53 or later
+- Exactly two observed images of identical dimensions acquired under identical imaging conditions
+
+### Download
+
+[GitHub Repository](https://github.com/Motohiro-TABUCHI/SNR_star_Tool)
+
+### Notes
+
+- Assumes additive, zero-mean, independent noise between the two images
+- Larger ROIs improve estimation stability
+- Negative covariance may indicate unsuitable imaging conditions
+
+### Reference
+
+{% include citation %}