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Hybrid image restoration using SWT based denoising and regularization in frequency domain

机译:混合图像恢复使用基于SWT的频域的基于SWT的去噪和正则化

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This paper presents a hybrid approach for image restoration which is degraded from known estimated blurring kernel, read out noise and photon counting noise. The novelty of the approach lies that it does not require noise power at the time of deconvolution while it accounts all possible noise, which occurred at the time of present acquisition of image. In the model, first stage is denoise the degraded image with use of Stationary Wavelet Transform (SWT) using soft threshold. And in second stage image regularization by maximum aposteriori. Test is performed on various real life single frame degraded image with noise. The approach shows the superiority of the scheme in term of subjective quality and increase in signal to noise ratio.
机译:本文提出了一种用于图像恢复的混合方法,其从已知的估计模糊内核中降解,读出噪声和光子计数噪声。 该方法的新颖性呈现,在核磁卷积时不需要噪声功率,而在当前采集图像时发生了所有可能的噪声。 在模型中,使用软阈值使用静止小波变换(SWT),第一阶段是Denoise Digaded图像。 并在第二阶段图像正规通过最大的Aposteriori。 对各种真实生活单帧进行测试,噪声下降图像降低图像。 该方法以主观质量的术语显示了方案的优越性,并增加了信噪比的信号。

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