Low dynamic range (LDR) image may contain low-light and highlight areas due to the limitations of the dynamic range of conventional image sensors. Low-light and highlight phenomena limit colour richness and visibility of objects in an image. Therefore, it can cause a reduction in the quality of images and a loss in accuracy in the application of image recognition. To overcome this, high dynamic range (HDR)-like images have been developed with rich colours such as those seen by the human eye. In this study, the authors propose a method to obtain an HDR-like image from a single LDR image by removing the specular component from highlight pixels as well as strengthening the actual colour. Next, they select low-light image enhancement via illumination map estimation as a low-light enhancement technique by showing the comparison with gamma-based expansion operator. They evaluate their HDR-like output images with non-reference and full-reference metrics. They show the comparison of their proposed method with six other methods. Besides, visually, their proposed method delivers more pleasing output than the output of other competitive methods.

中文翻译：

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结合了高光去除和低光图像增强技术，可生成类似HDR的图像

由于常规图像传感器的动态范围的限制，低动态范围（LDR）图像可能包含光线不足和高光区域。弱光和高光现象会限制图像中对象的色彩丰富度和可见度。因此，在图像识别的应用中会导致图像质量的下降和准确性的损失。为了克服这个问题，已经开发了具有丰富色彩的高动态范围（HDR）图像，例如人眼所见的色彩。在这项研究中，作者提出了一种从单个LDR图像中获得类似HDR图像的方法，方法是从高亮像素中删除镜面反射分量并增强实际颜色。下一个，他们通过显示与基于伽马的扩展算子的比较，选择了通过照明图估计的低光图像增强作为低光增强技术。他们使用非参考和完全参考指标评估其类似HDR的输出图像。他们展示了他们提出的方法与其他六种方法的比较。此外，从视觉上看，他们提出的方法比其他竞争方法的输出更具吸引力。