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Specular Reflection Detection and Substitution: A Key for Accurate Medical Image Analysis

机译:镜面反射检测和替代:准确医学图像分析的关键

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The quality of any image depends on the specifications of capturing devices. However, external factors also affect the appearance of an image. The disturbance created in image due to reflections from the surface is a major issue with respect to image quality reduction. These reflected regions appearing in image are called as specular reflections (SR). This problem is common in all types of images and it disturbs the image interpretation. Thus, the removal of SR pixels is one of the most important pre-processing steps for accurate image analysis. Several techniques are suggested in the literature to address this issue. The paper reports an in-depth review of various categories and issues of SR detection and the probable solution to overcome it. Experimental analysis proves that Kittler minimum error threshold selection method can be applied on input image as a preprocessing method for SR detection and analysis. Increase in Jaccard Index (JC) justifies the performance of proposed solution.
机译:任何图像的质量取决于捕获设备的规格。但是,外部因素也会影响图像的外观。由于表面的反射,图像中产生的干扰是关于图像质量降低的主要问题。出现在图像中的这些反射区域称为镜面反射(SR)。这个问题在所有类型的图像中都是常见的,并且它扰乱了图像解释。因此,去除SR像素是用于精确图像分析的最重要的预处理步骤之一。在文献中提出了几种技术来解决这个问题。本文报告了对SR检测的各类类别和问题的深入审查以及可能的解决方案来克服它。实验分析证明,可以在输入图像上应用Kittler最小误差阈值选择方法作为SR检测和分析的预处理方法。 Jaccard Index(JC)的增加证明了提出解决方案的性能。

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