Comparative evaluation of retrospective shading correction methods
Comparative evaluation of retrospective shading correction methods
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DOI：
10.1046/j.1365-2818.2002.01079.x
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发表时间：
2002-12-01
期刊：
影响因子：
--
通讯作者：
Pernus, F
中科院分区：
文献类型：
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作者：
Tomazevic, D;Likar, B;Pernus, F
由于图像形成过程的固有缺陷，显微图像经常被伪强度变化破坏。这种现象称为阴影或强度不均匀性，可能对自动图像处理（例如分割和配准）产生不利影响。阴影校正方法可以是前瞻性的或回顾性的。前者需要调整到阴影校正的采集协议，而后者可以应用于任何图像，因为它们只使用图像中已经存在的信息。九回顾阴影校正方法的实施，评估和比较三组不同结构的合成阴影和无阴影的图像和三组真实的显微镜图像由不同的采集设置。方法的性能用两个不同目标类之间的联合变异系数来定量表示。结果表明，除了熵最小化方法，所有的方法，工作对某些图像，但表现不佳的其他。熵最小化方法在减少真实强度变化和保持无阴影图像的强度特性方面优于其他方法。熵最小化方法的强度在应用于包含大规模对象的图像时尤其明显。
Because of the inherent imperfections of the image formation process, microscopical images are often corrupted by spurious intensity variations. This phenomenon, known as shading or intensity inhomogeneity, may have an adverse affect on automatic image processing, such as segmentation and registration. Shading correction methods may be prospective or retrospective. The former require an acquisition protocol tuned to shading correction, whereas the latter can be applied to any image, because they only use the information already present in an image. Nine retrospective shading correction methods were implemented, evaluated and compared on three sets of differently structured synthetic shaded and shading-free images and on three sets of real microscopical images acquired by different acquisition set-ups. The performance of a method was expressed quantitatively by the coefficient of joint variations between two different object classes. The results show that all methods, except the entropy minimization method, work well for certain images, but perform poorly for others. The entropy minimization method outperforms the other methods in terms of reduction of true intensity variations and preservation of intensity characteristics of shading-free images. The strength of the entropy minimization method is especially apparent when applied to images containing large-scale objects.