用于自然和医学图像的合适质量度量的识别

K. Thakur, Omkar H. Damodare, A. Sapkal
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引用次数: 6

摘要

图像去噪后的质量评价是图像去噪应用中的重要问题之一。直到今天,研究人员提出了许多具有各自特点的质量度量标准。在实际应用中,自然图像和医学图像的图像采集系统是不同的。因此,这些图像中引入的噪声在性质上也是不同的。考虑到这一事实,作者试图分别对高斯图像、散斑图像和泊松图像、超声图像和x射线图像确定合适的质量度量。本文从噪声方差的角度对全参考类的16种不同的质量度量进行了评价,并确定了适合于特定类型噪声的质量度量。在这项工作中,还确定了开发与噪声相关的质量度量的强烈需求。
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IDENTIFICATION OF SUITED QUALITY METRICS FOR NATURAL AND MEDICAL IMAGES
To assess quality of the denoised image is one of the important task in image denoising application. Numerous quality metrics are proposed by researchers with their particular characteristics till today. In practice, image acquisition system is different for natural and medical images. Hence noise introduced in these images is also different in nature. Considering this fact, authors in this paper tried to identify the suited quality metrics for Gaussian, speckle and Poisson corrupted natural, ultrasound and X-ray images respectively. In this paper, sixteen different quality metrics from full reference category are evaluated with respect to noise variance and suited quality metric for particular type of noise is identified. Strong need to develop noise dependent quality metric is also identified in this work.
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