Color Night Vision for Navigation and Surveillance

Abstract

Fusion of registered images of night scenery that are obtained from cameras tuned to different band-widths will be a significant component of future night-vision devices. A new algorithm for such multispectral image fusion is described. The algorithm performs gray-scale image fusion using a method based on principal components. The monochrome fused image is then colored by means of a suitable pseudocoloring technique to produce the fused color output image. The approach can easily be used for any number of bandwidths. Examples illustrate the algorithm’s use to fuse an intensified low-light visible image with another image obtained from a single forward-looking infrared camera. The algorithm may be implemented readily in hardware for use in night-vision devices as an important aid to surveillance and navigation in total darkness. The applicability of the technology to transportation is also discussed.

Fast natural color mapping for night-time imagery

“…The two most common night-time imaging systems are low-light-level (e.g. image-intensified) cameras, which amplify the reflected visible to near-infrared (VNIR) light, and thermal infrared (IR) cameras, which convert thermal energy from the midwave (3-5 lm) or the long wave (8)(9)(10)(11)(12) lm) part of the spectrum into a visible image.…”

Implementation of Max Principle with PCA in image fusion for Surveillance and Navigation Application

“…Under the statistical fusion schemes are the principle component transform (PCA) analysis, regression variable substitution [12,13] and the canonical variate substitution [14] algorithms. Burke developed an image fusion algorithm using principle component analysis [15] and Das et al proposed a PCA based image fusion technique for night vision application [16]. Also hybrid techniques have been proposed; such as the advanced wavelet transform (aDWT) method by Zheng et al [17] that incorporates principle component analysis and morphological processing into a regular DWT fusion algorithm.…”

“…This is achieved by the use of multiple sensors to obtain the visual information and by utilizing the synergism of different imaging sensors for better situation assessment [4]. Presently, the focus is on the fusion of infrared (IR) images along with visible images obtained using charge coupled device (CCD) cameras [1,5]. The infrared image is a map of the infrared radiations which are emitted by objects having a temperature above absolute zero, the amount of radiation emitted being partly governed by the object's temperature.…”

Contrast Enhanced Low-light Visible and Infrared Image Fusion

“…Several fusion methods for low-light visible and infrared image fusion have been proposed by researchers [7][8][9] . Generally, pixel-based fusion methods are employed for fusion as they are simple to implement as compared with the computational complexity in implementing region-based and feature-based fusion techniques.…”