IEEE Trans Biomed Circuits Syst. 2018 Oct;12(5):993-1003. doi: 10.1109/TBCAS.2018.2869530.
Good image quality of the wireless capsule endoscopy (WCE) is the key for doctors to diagnose gastrointestinal (GI) tract diseases. However, the poor illumination, limited performance of the camera in WCE, and complex environment in the GI tract usually result in low-quality endoscopic images. Existing image enhancement methods only use the information of the image itself or multiple images of the same scene to accomplish the enhancement. In this paper, we propose an adaptive image enhancement method based on guide image and fraction-power transformation. First, intensities of endoscopic images are analyzed to assess the illumination conditions. Second, images captured under poor illumination conditions are enhanced by a brand-new image enhancement method called adaptive guide image based enhancement (AGIE). AGIE enhances low-quality images by using the information of a good quality image of the similar scene. Otherwise, images are enhanced by the proposed adaptive fraction-power transformation. Experimental results show that the proposed method improves the average intensity of endoscopic images by 64.20% and the average local entropy by 31.25%, which outperforms the state-of-art methods.
无线胶囊内镜（WCE）的良好图像质量是医生诊断胃肠道（GI）疾病的关键。然而，WCE 中的照明条件差、相机性能有限以及 GI 道中的复杂环境通常会导致低质量的内窥镜图像。现有的图像增强方法仅使用图像本身或同一场景的多个图像的信息来完成增强。在本文中，我们提出了一种基于引导图像和分数幂变换的自适应图像增强方法。首先，分析内窥镜图像的强度以评估照明条件。其次，通过一种称为自适应引导图像增强（AGIE）的全新图像增强方法来增强在光照条件差的情况下拍摄的图像。AGIE 通过使用相似场景的高质量图像的信息来增强低质量图像。否则，通过所提出的自适应分数幂变换来增强图像。实验结果表明，所提出的方法将内窥镜图像的平均强度提高了 64.20%，平均局部熵提高了 31.25%，优于最先进的方法。
