论文标题
使用亮色，clahe和Etinex进行预处理图像
Pre-processing Image using Brightening, CLAHE and RETINEX
论文作者
论文摘要
本文着重于查找三种图像增强算法的最佳预处理方法：亮亮，clahe和otininex。为了进行图像训练的目的，这些方法将组合在一起，以找出图像增强的最佳方法。我们已经对三种方法的不同排列进行了研究：亮点，克拉赫和视网膜。该评估基于应用于所有处理图像的精美边缘检测。然后，与图像之间的真实正像素编号相比，对象的清晰度将是合理的。在图像上使用了不同的数字组合预处理功能后，Clahe被证明是最有效的边缘改进，亮度对增强边缘的影响不会太大，而Estinex甚至降低了图像的清晰度，并且对图像增强的贡献很小。
This paper focuses on finding the most optimal pre-processing methods considering three common algorithms for image enhancement: Brightening, CLAHE and Retinex. For the purpose of image training in general, these methods will be combined to find out the most optimal method for image enhancement. We have carried out the research on the different permutation of three methods: Brightening, CLAHE and Retinex. The evaluation is based on Canny Edge detection applied to all processed images. Then the sharpness of objects will be justified by true positive pixels number in comparison between images. After using different number combinations pre-processing functions on images, CLAHE proves to be the most effective in edges improvement, Brightening does not show much effect on the edges enhancement, and the Retinex even reduces the sharpness of images and shows little contribution on images enhancement.
