英语翻译Night Removal is highly desired in both computational photography and computer vision applications.However,few works have been studied towards this goal.This paper proposes an effective algorithm for removing the night from a single input
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英语翻译Night Removal is highly desired in both computational photography and computer vision applications.However,few works have been studied towards this goal.This paper proposes an effective algorithm for removing the night from a single input
英语翻译
Night Removal is highly desired in both computational photography and computer vision applications.
However,few works have been studied towards this goal.This paper proposes an effective algorithm for removing the night from a single input image.We present a new Color Estimation Model (CEM) for transforming the image from “night” to “day” - along with a guided statistical Dark-to-Day (D2D) prior directing for performance optimization.To restore the noisy and blurred image after CEM,sparse representation based on dozens of corresponding day-time images in different illuminations as dictionary training set is used in our algorithm.Extensive experiments on natural images show our algorithm can achieve convincing results.
英语翻译Night Removal is highly desired in both computational photography and computer vision applications.However,few works have been studied towards this goal.This paper proposes an effective algorithm for removing the night from a single input
晚上搬家是高度期望的计算摄影和计算机视觉应用.
然而,很少有著作研究了实现这一目标.本文提出了一种有效的算法把晚上从一个输入图像.我们提出一个新的颜色估计模型(CEM)将图像从“夜”,“天”——以及引导统计Dark-to-Day(D2D)之前指挥的性能优化.恢复嘈杂和杰姆模糊图像后,稀疏的最大