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A ghostfree contrast enhancement method for multiview images without depth information
Journal of Visual Communication and Image Representation ( IF 2.6 ) Pub Date : 2021-06-03 , DOI: 10.1016/j.jvcir.2021.103175
Rizwan Khan , You Yang , Qiong Liu , Zahid Hussain Qaisar

High dynamic range (HDR) images greatly improve visual content quality, but pose challenges in processing, acquisition, and display. Images captured in real-world scenarios with multiple nonlinear cameras, extremely short unknown exposure time, and a shared light source present the additional challenges of incremental baseline and angle deviation amongst the cameras. The disparity maps in such conditions are not reliable; therefore, we propose a method that relies on the accurate detection and matching of feature points across adjacent viewpoints. We determine the exposure gain among the matched feature points in the involved views and design an image restoration method to restore multiview low dynamic range (MVLDR) images for each viewpoint. Finally, the fusion of these restored MVLDR images produces high-quality images for each viewpoint without capturing a series of bracketed exposure. Extensive experiments are conducted in controlled and uncontrolled conditions, and results prove that the proposed method competes for the state-of-the-arts.



中文翻译:

一种无深度信息的多视点图像无重影对比度增强方法

高动态范围 (HDR) 图像极大地提高了视觉内容质量,但在处理、采集和显示方面带来了挑战。在具有多个非线性相机、极短的未知曝光时间和共享光源的真实场景中捕获的图像带来了相机之间增量基线和角度偏差的额外挑战。这种情况下的视差图是不可靠的;因此,我们提出了一种依赖于相邻视点之间特征点的准确检测和匹配的方法。我们确定相关视图中匹配特征点之间的曝光增益,并设计一种图像恢复方法来恢复每个视点的多视图低动态范围 (MVLDR) 图像。最后,这些恢复的 MVLDR 图像的融合为每个视点生成高质量图像,而无需捕获一系列包围曝光。在受控和非受控条件下进行了大量实验,结果证明所提出的方法可以与最先进的方法竞争。

更新日期:2021-06-10
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