Enhancing scene perception using a multispectral fusion of visible–near‐infrared image pair

Abstract

In this study, a method for fusing of visible (or standard RGB) with near‐infrared (NIR) image pair for enhancing a hazy image is proposed. Better image enhancement in terms of contrast, sharpness, increased perception is realised by combining the components from both the spectra. While there are a number of applications that use NIR images, very few combine RGB and NIR information of the same scene taken from two separate imaging devices. Although NIR images are greyscaled in nature, they have intrinsic properties desirable in both colour and visible imagery of a number of scenes. Instances are increased the contrast between sky and clouds; shadowed and non‐shadowed regions; and increased optical depth. These features are in most cases missed by a standard RGB camera and therefore, a fusion of such RGB–NIR image pairs is highly beneficial. The scheme for fusing these image pairs is realised by using a novel, fuzzy clustering algorithm along with wavelet transform so that not only contrast and sharpness are enhanced, but also the chromaticity of the original RGB image is retained. The proposed technique is well demonstrated for various outdoor scenes, and better results are obtained when compared against some of the state‐of‐the‐art techniques proposed recently.

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].…”

Improving multispectral pedestrian detection with scale‐aware permutation attention and adjacent feature aggregation

“…Thermal images generate a lot of noise interference during the day, thus thermal images are usually used for detection at night. Pedestrian detection introduces multispectral images to train the model [1][2][3][4], which allows for better detection of pedestrians under complex lighting compared to singlemodal images. Similarly, the results of pedestrian detection on small scale are still unsatisfactory.…”