Abstract
The noise distribution of images obtained by X-ray sensors in low-dosage situations can be analyzed using the Poisson and Gaussian mixture model. Multiscale conversion is one of the most popular noise reduction methods used in recent years. Estimation of the noise distribution of each subband in the multiscale domain is the most important factor in performing noise reduction, with non-subsampled contourlet transform (NSCT) representing an effective method for scale and direction decomposition. In this study, we use artificially generated noise to analyze and estimate the Poisson–Gaussian noise of low-dose X-ray images in the NSCT domain. The noise distribution of the subband coefficients is analyzed using the noiseless low-band coefficients and the variance of the noisy subband coefficients. The noise-after-transform also follows a Poisson–Gaussian distribution, and the relationship between the noise parameters of the subband and the full-band image is identified. We then analyze noise of actual images to validate the theoretical analysis. Comparison of the proposed noise estimation method with an existing noise reduction method confirms that the proposed method outperforms traditional methods.
Highlights
Since their discovery by Röntgen, X-rays have been the subject of research in a broad variety of fields
X-ray image sensor noise comprises Poisson noise originating from X-ray photons and Gaussian noise generated in the sensor
The results reveal that the noise in the non-subsampled contourlet transform (NSCT) subband has a Poisson–Gaussian distribution comprising multiscale, low-band dependent Poisson noise and signal-independent Gaussian noise
Summary
Since their discovery by Röntgen, X-rays have been the subject of research in a broad variety of fields. A typical wavelet transform does not have optimal properties for the analysis of two-dimensional signals such as natural images To overcome these drawbacks, multiscale and directional representations have recently been proposed. CT has a shift-variance property, with produced values changing according to sub-sampling position To solve this problem, a non-subsampled contourlet transform (NSCT) was proposed in [24]. We analyze the Poisson–Gaussian noise for low-dose X-ray images in the NSCT domain, and show that it has a Poisson–Gaussian distribution. To confirm the consistency of this theoretical analysis with the actual results, we analyze the noise distribution of the actual low-dose X-ray images in the NSCT domain. The results of noise reduction using proposed noise analysis and estimation method are compared with those obtained from a conventional method in Section 5 and, Section 6 presents our conclusions and future work
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