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A Novel Method for the Removal of High Density Salt and Pepper Noise in Grayscale and Color Images

机译:去除灰度和彩色图像中高密度盐和胡椒噪声的新方法

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Mean of unsymmetrical trimmed variants is used as a detector for the detection of fixed valued impulse noise is proposed. A fixed 3x3 window is kept constant for the increasing noise densities. The processed pixel is considered as noisy if the absolute difference between processed pixels and mean of unsymmetrical trimmed variants is greater than fixed threshold. Under high noise densities if the processed pixel is noisy and computed median is also noisy then replace the processed pixel with mean of unsymmetrical trimmed variants else if the processed pixel is noisy and computed median is not noisy then the corrupted pixel is replaced by computed median else the pixel is termed uncorrupted and it is left unaltered. If the entire pixels of the current processing window are noisy then global mean of the image is replaced as output. The Proposed Algorithm (PA) is tested on different varying detail images. The proposed algorithm is compared with the standard algorithms and found to give good results both qualitative and quantitatively for increasing noise densities.
机译:非对称的修整变量的平均值被用作检测器,用于检测固定值的脉冲噪声。为了增加噪声密度,固定的3x3窗口保持恒定。如果处理后的像素与非对称修剪变体均值之间的绝对差大于固定阈值,则认为处理后的像素有噪声。在高噪声密度下,如果处理后的像素有噪点,并且计算出的中位数也有噪点,则用不对称修整变量的平均值替换处理后的像素,否则,如果处理后的像素有噪点并且计算出的中位数不噪杂,则将损坏的像素替换为计算出的中值该像素被称为未损坏,并且保持不变。如果当前处理窗口的整个像素都嘈杂,则将图像的全局平均值替换为输出。建议算法(PA)在不同的变化细节图像上进行了测试。将所提出的算法与标准算法进行比较,发现在提高噪声密度方面,定性和定量都给出了良好的结果。

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