The main purpose of image enhancement technology is to improve the quality of the image to better assist those activities of daily life that are widely dependent on it like healthcare, industries, education, and surveillance. Due to the influence of complex environments, there are risks of insufficient detail and low contrast in some images. Existing enhancement algorithms are prone to overexposure and improper detail processing. This paper attempts to improve the treatment effect of Phase Stretch Transform (PST) on the information of low and medium frequencies. For this purpose, an image enhancement algorithm on the basis of fractional-order PST and relative total variation (FOPSTRTV) is developed to address the task. In this algorithm, the noise in the original image is removed by low-pass filtering, the edges of images are extracted by fractional-order PST, and then the images are fused with extracted edges through RTV. Finally, extensive experiments were used to verify the effect of the proposed algorithm with different datasets.

中文翻译：

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基于分数阶相位拉伸变换和相对总变化的图像增强算法

图像增强技术的主要目的是提高图像质量，以更好地辅助那些广泛依赖于日常生活的活动，例如医疗保健，工业，教育和监视。由于复杂环境的影响，某些图像中存在细节不足和对比度低的风险。现有的增强算法易于过度曝光和不正确的细节处理。本文试图提高相位扩展变换（PST）对低频和中频信息的治疗效果。为此，开发了一种基于分数阶PST和相对总变化量（FOPSTRTV）的图像增强算法来解决该任务。在此算法中，原始图像中的噪声通过低通滤波消除，通过分数阶PST提取图像的边缘，然后通过RTV将图像与提取的边缘融合。最后，大量实验被用来验证所提出算法在不同数据集中的效果。