A Blurring Index for Medical Images |
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Authors: | Tzong-Jer Chen PhD Keh-Shih Chuang Jen-Hao Chang Ya-Hui Shiao Chun-Chao Chuang |
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Institution: | (1) Department of Medical Imaging Technology, Shu-Zen College of Medicine and Management, Luju Shiang, Kaohsiung, 82144, Taiwan;(2) Department of Nuclear Science, National Tsing-Hua University, Taiwan;(3) Biomedical Engineering Center, Industrial Technology Research Institute, Chutung, Hsinchu, Taiwan |
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Abstract: | This study was undertaken to investigate a useful image blurring index. This work is based on our previously developed method,
the Moran peak ratio. Medical images are often deteriorated by noise or blurring. Image processing techniques are used to
eliminate these two factors. The denoising process may improve image visibility with a trade-off of edge blurring and may
introduce undesirable effects in an image. These effects also exist in images reconstructed using the lossy image compression
technique. Blurring and degradation in image quality increases with an increase in the lossy image compression ratio. Objective
image quality metrics e.g., normalized mean square error (NMSE)] currently do not provide spatial information about image
blurring. In this article, the Moran peak ratio is proposed for quantitative measurement of blurring in medical images. We
show that the quantity of image blurring is dependent upon the ratio between the processed peak of Moran's Z histogram and the original image. The peak ratio of Moran's Z histogram can be used to quantify the degree of image blurring. This method produces better results than the standard gray
level distribution deviation. The proposed method can also be used to discern blurriness in an image using different image
compression algorithms. |
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Keywords: | Moran peak ratio image blurring image quality |
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