Tran Van Luan, Lin Huei-Yung
Department of Electrical Engineering, National Chung Cheng University, Chiayi 621, Taiwan.
Department of Electrical Engineering, Advanced Institute of Manufacturing with High-Tech Innovation, National Chung Cheng University, Chiayi 621, Taiwan.
Sensors (Basel). 2020 Jul 16;20(14):3950. doi: 10.3390/s20143950.
Extending the dynamic range can present much richer contrasts and physical information from the traditional low dynamic range (LDR) images. To tackle this, we propose a method to generate a high dynamic range image from a single LDR image. In addition, a technique for the matching between the histogram of a high dynamic range (HDR) image and the original image is introduced. To evaluate the results, we utilize the dynamic range for independent image quality assessment. It recognizes the difference in subtle brightness, which is a significant role in the assessment of novel lighting, rendering, and imaging algorithms. The results show that the picture quality is improved, and the contrast is adjusted. The performance comparison with other methods is carried out using the predicted visibility (HDR-VDP-2). Compared to the results obtained from other techniques, our extended HDR images can present a wider dynamic range with a large difference between light and dark areas.
扩展动态范围可以呈现出比传统低动态范围（LDR）图像更丰富的对比度和物理信息。为了解决这个问题，我们提出了一种从单张LDR图像生成高动态范围图像的方法。此外，还引入了一种用于高动态范围（HDR）图像直方图与原始图像匹配的技术。为了评估结果，我们利用动态范围进行独立的图像质量评估。它能够识别出细微亮度差异，这在评估新型照明、渲染和成像算法中起着重要作用。结果表明，图像质量得到了改善，对比度也得到了调整。使用预测可见性（HDR-VDP-2）与其他方法进行了性能比较。与其他技术获得的结果相比，我们扩展的HDR图像可以呈现出更宽的动态范围，亮区和暗区之间有很大差异。
