图像融合
人工智能
计算机视觉
计算机科学
融合
合并(版本控制)
亮度
高动态范围
复合图像滤波器
高斯分布
高斯滤波器
图像(数学)
动态范围
模式识别(心理学)
光学
物理
哲学
量子力学
语言学
情报检索
作者
Zhengguo Li,Zhe Wei,Changyun Wen,Jinghong Zheng
标识
DOI:10.1109/tip.2017.2651366
摘要
Multi-scale exposure fusion is an effective image enhancement technique for a high dynamic range (HDR) scene. In this paper, a new multi-scale exposure fusion algorithm is proposed to merge differently exposed low dynamic range (LDR) images by using the weighted guided image filter to smooth the Gaussian pyramids of weight maps for all the LDR images. Details in the brightest and darkest regions of the HDR scene are preserved better by the proposed algorithm without relative brightness change in the fused image. In addition, a new weighted structure tensor is introduced to the differently exposed images and it is adopted to design a detail extraction component for the proposed fusion algorithm, such that users are allowed to manipulate fine details in the enhanced image according to their preference. The proposed multi-scale exposure fusion algorithm is also applied to design a simple single image brightening algorithm for both low-light imaging and back-light imaging.
科研通智能强力驱动
Strongly Powered by AbleSci AI