Real time Tarp-linear estimator for image noise reduction

U. Ali, S.A. Khan
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Abstract

Many efficient wavelet domain estimation algorithms for noise reduction have been proposed in the literature. All of them are based on variance estimation, which require all wavelet coefficients to be saved in the memory thus causing constrains towards the development of real time system. Tarp filter has been used successfully for online/real-time variance estimation of the multilevel wavelets and has shown exceptional performance in image compression. This paper proposes the utilization of the Tarp filter for the estimation of wavelet coefficient variance without saving them in memory. The paper presents the results for Tarp-linear estimator (TLE) and compares it with simple linear estimator (LE). It is found that TLE, while having an advantage of memory free noise reduction method, compromise on SNR
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用于图像降噪的实时tarp -线性估计
文献中提出了许多有效的小波域估计降噪算法。这些方法都是基于方差估计,需要将所有的小波系数保存在存储器中,这对实时系统的开发造成了制约。Tarp滤波器已成功地用于在线/实时多电平小波方差估计,并在图像压缩中显示出优异的性能。本文提出了在不占用内存的情况下,利用Tarp滤波器估计小波系数方差的方法。本文给出了tarp -线性估计量(TLE)的结果,并与简单线性估计量(LE)进行了比较。结果表明,该方法虽然具有无存储器降噪方法的优点,但在信噪比上有所妥协
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