Visible and Near-Infrared Image Acquisition and Fusion for Night Surveillance

Abstract

Image fusion combines images with different information to create a single, information-rich image. The process may either involve synthesizing images using multiple exposures of the same scene, such as exposure fusion, or synthesizing images of different wavelength bands, such as visible and near-infrared (NIR) image fusion. NIR images are frequently used in surveillance systems because they are beyond the narrow perceptual range of human vision. In this paper, we propose an infrared image fusion method that combines high and low intensities for use in surveillance systems under low-light conditions. The proposed method utilizes a depth-weighted radiance map based on intensities and details to enhance local contrast and reduce noise and color distortion. The proposed method involves luminance blending, local tone mapping, and color scaling and correction. Each of these stages is processed in the LAB color space to preserve the color attributes of a visible image. The results confirm that the proposed method outperforms conventional methods.

High-Efficiency Integrated Color Routers by Simple Identical Nanostructures for Visible and Near-Infrared Wavelengths

“…The NIR light also has stronger penetration and smaller scattering of the air particles than the visible light. Hence, the fusion of visible and NIR light can be used for weak-light imaging [5][6][7][8][9][10][11].…”

Enhancing infrared color reproducibility through multispectral image processing using RGB and three infrared channels

“…[1][2][3][4] Another approach involves combining VIS and infrared (IR) light by obtaining luminance information from the sensor response of IR and synthesizing color information from the sensor response of VIS light so that color image representation can be used, even in dim environments. [5][6][7][8][9][10][11][12][13] However, neither of these methods can be used to obtain color information in the complete absence of VIS light. To solve this problem, the usual approach is color estimation of monochrome images.…”

Tone Image Classification and Weighted Learning for Visible and NIR Image Fusion

“…A color camera uses an infrared cut-off filter, which blocks an infrared signal, to take a visible light image. Infrared light influx distorts color information, and in particular, since the amount of light in the daytime is highly intense, infrared light can easily saturate the image [ 1 , 2 ]. However, since the infrared image contains detailed information that is not expressed in the visible light image, the visibility of the image can be improved by the information fusion method.…”