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基于非均匀对比度拉伸和强度传递的模糊视网膜图像增强。

Enhancement of blurry retinal image based on non-uniform contrast stretching and intensity transfer.

机构信息

School of Information and Electronics, Beijing Institute of Technology, Beijing, 100081, China.

出版信息

Med Biol Eng Comput. 2020 Mar;58(3):483-496. doi: 10.1007/s11517-019-02106-7. Epub 2020 Jan 2.

Abstract

Proper contrast and sufficient illuminance are important in clearly identifying the retinal structures, while the required quality cannot always be guaranteed due to major reasons like acquisition process and diseases. To ensure the effectiveness of enhancement, two solutions are developed for blurry retinal images with sufficient illuminance and insufficient illuminance, respectively. The proposed contrast stretching and intensity transfer are main steps in both of the two solutions. The contrast stretching is based on base-intensity removal and non-uniform addition. We assume that a base-intensity exists in an image, which mainly supports the basic illuminance but has less contribution to texture information. The base-intensity is estimated by the constrained Gaussian function and then removed. The non-uniform addition using compressed Gamma map is further developed to improve the contrast. Additionally, an effective intensity transfer strategy is introduced, which can provide required illuminance for a single channel after contrast stretching. The color correction can be achieved if the intensity transfer is performed on three channels. Results show that the proposed solutions can effectively improve the contrast and illuminance, and good visual perception for quality degraded retinal images is obtained. Illustration of contrast stretching based on a signal colour channel.

摘要

适当的对比度和充足的光照度对于清晰识别视网膜结构非常重要,但由于采集过程和疾病等主要原因,并不总能保证所需的质量。为了确保增强效果,我们为光照充足但光照不足的模糊视网膜图像分别开发了两种解决方案。所提出的对比度拉伸和强度传递是这两种解决方案的主要步骤。对比度拉伸基于基础强度去除和非均匀添加。我们假设图像中存在一个基础强度,它主要支持基本光照度,但对纹理信息的贡献较小。通过约束高斯函数对基础强度进行估计,然后将其去除。进一步开发了使用压缩伽马图的非均匀添加,以提高对比度。此外,引入了一种有效的强度传递策略,该策略可以在对比度拉伸后为单个通道提供所需的光照度。如果在三个通道上执行强度传递,则可以实现颜色校正。结果表明,所提出的解决方案可以有效地提高对比度和光照度,从而获得质量下降的视网膜图像的良好视觉感知。基于信号颜色通道的对比度拉伸示意图。

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