Abstract

Image processing continues to be a challenging topic in many scientific fields such as medicine, computational physics and informatics especially with the discovery and development of 3D cases. Therefore, development of suitable tools that guarantee a best treatment is a necessity. Spherical shapes are a big class of 3D images whom processing necessitates adoptable tools. This encourages researchers to develop special mathematical bases suitable for 3D spherical shapes. The present work lies in this whole topic with the application of special spherical harmonics bases. In Jallouli et al. (Soft Comput 2018. https://doi.org/10.1007/s00500-018-3596-9), theoretical framework of spherical harmonics filters adapted to image processing has been developed. In the present paper, new approach based on Jallouli et al. (Soft Comput 2018. https://doi.org/10.1007/s00500-018-3596-9) is proposed for the reconstruction of images provided with spherical harmonics Shannon-type entropy to evaluate the order/disorder of the reconstructed image. Efficiency and accuracy of the approach are demonstrated by a simulation study on several spherical models.

中文翻译：

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向递归球面谐波发布双滤波器：第二部分：用于优化建模的相关球面谐波熵

摘要

在许多科学领域，例如医学，计算物理学和信息学中，图像处理仍然是一个具有挑战性的主题，尤其是在3D病例的发现和开发中。因此，有必要开发确保最佳治疗的合适工具。球形形状是一大类3D图像，对其进行处理需要采用可采用的工具。这鼓励研究人员开发适合3D球形的特殊数学基础。目前的工作是在整个主题中使用特殊的球谐基频进行的。在Jallouli等人中。（软计算2018.https ： //doi.org/10.1007/s00500-018-3596-9），已开发出适用于图像处理的球谐滤波器的理论框架。在本文中，基于Jallouli等人的新方法。（Soft Comput 2018. https://doi.org/10.1007/s00500-018-3596-9）提出用于重建具有球谐谐波Shannon型熵的图像，以评估重建图像的有序/无序。通过对几个球形模型的仿真研究证明了该方法的效率和准确性。