Efficient and Adaptive Tone Mapping Algorithm Based on Guided Image Filter
Efficient and Adaptive Tone Mapping Algorithm Based on Guided Image Filter
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DOI：
10.1142/s0218001420540129
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发表时间：
2020-04-01
影响因子：
1.5
通讯作者：
Zhang, Wenting
中科院分区：
文献类型：
--
作者：
Jia, Yuan;Zhang, Wenting
计算机视觉算法的识别率在很大程度上依赖于图像质量。为了提高高动态范围(HDR)场景下采集的图像的视觉质量，提出了一种基于引导图像滤波(GIF)的高效自适应色调映射算法。HDR图像根据其平均亮度进行自适应压缩。然后使用引导图像过滤器将其分解为基本层和细节层。我们同时对基本层和细节层进行改进，并将这两层结合在一起得到最终的低动态范围(LDR)图像。由于这些参数与图像统计相关联，因此它们可以自适应地适应各种类型的图像。在HDR图像集上的客观评价结果表明了该算法的优越性。同时，通过主观观察，我们的算法结果可以减少晕圈伪影，并保留更多的细节。
The recognition rate of computer vision algorithms is highly dependent on the image quality. To enhance the visual quality of the images captured under high-dynamic range (HDR) scenes, we propose an efficient and adaptive tone mapping algorithm based on guided image filter (GIF). The HDR image is compressed adaptively according to its average luminance. Then we decompose it into a base layer and a detail layer using the guided image filter. We improve the base layer and enhance the detail layer simultaneously, and combine the two layers to get the final low-dynamic range (LDR) image. Since the parameters are linked with image statistics, they adaptively fit to various kinds of images. The objective evaluation results on HDR image sets demonstrate the superiority of our proposed algorithm. Meanwhile, the result of our algorithm can reduce the halo artifacts and preserve more detail by subjective observation.