PLANAR SCINTIGRAPHY IMAGE DE-NOISING USING COIFLET WAVELET

Ayu Jati Puspitasari, Ika Cismila Ningsih, Muhammad Sulthonur Ridwan, H. Hamadi
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Abstract

The planar scintigraphic image usually has poor resolution and contains noise. This noise can be removed using the coiflet wavelet method so that the image quality gets better. This coiflet wavelet method is a noise reduction method based on frequency analysis. The planar scintigraphy image is the reconstructed image of the gamma radiation count data (phantom with the Cs-137 source in it). The original image is 15×15 pixel. Before the de-noising process, the image went through an interpolation process, which is to increase the pixel size of the image. The original image enlarged to 70×70, 480×480, and 1200×1200 pixel. After de-noising with coiflet wavelet, the image quality is measured based on MSE and PSNR parameters. The resulting images are quite good, with MSE values are close to zero and PSNR values of more than 60 dB. The smaller the MSE and the bigger the PSNR, is getting the better the image quality. In this study, the results show that the 1200×1200 pixel image has the best quality. It means that the image enlargement process has a good effect on the de-noising process, especially if the original image has a low resolution.
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基于螺旋小波的平面闪烁图像去噪
平面闪烁图像通常分辨率较差,且含有噪声。利用coiflet小波方法可以去除这些噪声,从而提高图像质量。螺旋小波法是一种基于频率分析的降噪方法。平面闪烁图像是伽马辐射计数数据的重建图像(其中含有Cs-137源的幻像)。原始图像为15×15像素。在去噪之前,对图像进行插值处理,即增加图像的像素大小。将原始图像放大到70×70、480×480和1200×1200像素。用coiflet小波去噪后,基于MSE和PSNR参数测量图像质量。得到的图像效果非常好,MSE值接近于零,PSNR值大于60 dB。MSE越小,PSNR越大,图像质量越好。在本研究中,结果表明1200×1200像素图像的质量最好。这意味着图像放大过程对去噪过程有很好的效果,特别是在原始图像分辨率较低的情况下。
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