Authors:
Bong-Seok Choi
;
Dae-Chul Kim
;
Wang-Jun Kyung
and
Yeong-Ho Ha
Affiliation:
Kyungpook National University, Korea, Republic of
Keyword(s):
Multi-spectral Flash, Weight Map, Computational Photography.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Image Enhancement and Restoration
;
Image Formation and Preprocessing
Abstract:
Long exposure shot and flash lights are generally used to acquire images under low-light environments. However, flash lights often induce color distortion, red-eye effect, and they can disturb the subject. The other hand, long-exposure shots are prone to motion-blur due to camera shake or subject-motion. Recently, multi-spectral flash imaging has been introduced to overcome the limitations of traditional low-light photography. Multi-spectral flash imaging is performed by combining the invisible and visible spectrum information. However, common multi spectral flash approaches induce color distortion due to the lower accuracy of the invisible spectrum image. In this paper, we propose a multi-spectral flash imaging algorithm using optimization with weight map in order to improve color accuracy and brightness of image. The UV/IR and visible spectrum images are firstly captured, respectively. Then, to compensate luminance value under low light condition, tone reproduction is performed by
using adaptive curve due to image features that is obtained by Naka-Rushton formula. Next, to discriminate uniform regions from detail regions, weight map is generated by using Canny operator. Finally, the optimization object function takes into account the output likelihood with respect to the visible light image, the sparsity of image gradients as well as the spectral constraints for the IR-red channels and UV-blue channels. The performance of the proposed method has been subjectively evaluated using z-score, and we also show that output images have improved color accuracy and lower noise with respect to other methods.
(More)