Image fusion of complementary broadband spectral modalities has been extensively studied for providing performance enhancements to various military applications. With the growing availability of COTS and customized video cameras that image in VIS-NIR, SWIR, MWIR and LWIR, there is a corresponding increase in the practical exploitation of different combinations of fusion between any of these respective spectrums. Equinox Corporation has been developing a unique line of products around the concept of a single unified video image fusion device that can centrally interface with a variety of input cameras and output displays, together with a suite of algorithms that support image fusion across the diversity of possible combinations of these imaging modalities. These devices are small in size, lightweight and have power consumption in the vicinity of 1.5 Watts making them easy to integrate into portable systems.
Equinox Corporation has developed two new video board products for real-time image fusion of visible (or intensified visible/near-infrared) and thermal (emissive) infrared video. These products can provide unique capabilities to the dismounted soldier, maritime/naval operations and Unmanned Aerial Vehicles (UAVs) with low-power, lightweight, compact and inexpensive FPGA video fusion hardware. For several years Equinox Corporation has been studying and developing image fusion methodologies using the complementary modalities of the visible and thermal infrared wavebands including applications to face recognition, tracking, sensor development and fused image visualization. The video board products incorporate Equinox's proprietary image fusion algorithms into an FPGA architecture with embedded programmable capability. Currently included are (1) user interactive image fusion algorithms that go significantly beyond standard "A+B" fusion providing an intuitive color visualization invariant to distracting illumination changes, (2) generalized image co-registration to compensate for parallax, scale and rotation differences between visible/intensified and thermal IR, as well as non-linear optical and display distortion, and (3) automatic gain control (AGC) for dynamic range adaptation.
Recent research has demonstrated distinct advantages using thermal infrared imaging for improving face recognition performance. While conventional video cameras sense reflected light, thermal infrared cameras primarily measure emitted radiation from objects at just above room temperature (e.g., faces). Visible and thermal infrared image data collections of frontal views of faces have been on-going at NIST for over two years producing the most comprehensive database known to involve thermal infrared imagery of human faces. Rigorous experimentation with this database has revealed consistently superior recognition performance of algorithms when applied to thermal infrared particularly under variable illumination conditions. An end-to-end face recognition system incorporating simultaneous coregistered thermal infrared and visible has been developed and tested both indoors and outdoors with good performance.
Over the last decade there has been study of separating ground objects from background using multispectral imagery in the reflective spectrum from 400-2500nm. In this paper we explore using two broadband spectral modalities; visible and ShortWave InfraRed (SWIR),
for detection of minelike objects, obstacles and camouflage. Whereas multispectral imagery is sensed over multiple narrowband wavelengths, sensing over two broadband spectrums has the advantage of increased signal rsulting from integrated energy over larger spectrums. Preliminary results presented here show that very basic image fusion processing applied to visible and SWIR imagery produces reasonable illumination invariant segmentation of objects against background. This suggests the use of a simplified compact camera architecture using visible and SWIR sensing focal plane arrays for performing detection of mines and other important objects of interest.
A key issue for face recognition has been accurate identification under variable illumination conditions. Conventional video cameras sense reflected light so that image gray values are a product of both intrinsic skin reflectivity and external incident illumination, obfuscating intrinsic reflectivity of skin. It has been qualitatively observed that thermal imagery of human faces is invariant to changes in indoor and outdoor illumination, although there never has been any rigorous quantitative analysis to confirm this assertion published in the open literature. Given the significant potential improvement to the performance of face recognition algorithms using thermal IR imagery, it is important ot quantify observed illumination invariance and to establish a solid physical basis for this phenomenon. Image measurements are presented from two of the primarily used spectral regions for thermal IR; 3-5 micron MidWave IR and the 8-14 micron LWIR. All image measurements are made with respect to precise blackbody ground-truth. Radiometric calibration procedures for two different kinds of thermal IR sensors are presented and are emphasized as being an integral part to data collection protocols and face recognition algorithms.
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