In infrared scanning imaging system, long linear-array detector is needed for large field of view. Instead of using long
linear-array detector, we couple a non-conventional Infrared (IR) fiber bundle to a small scale Infrared Focal Plane Array
(IRFPA) whose format is 320×256 in system to implement 1024×4 format linear array imaging. The input of fiber bundle
is long linear array while output is plane-array. Fibers in IR fiber bundle are one to one mapping. Input end of fiber
bundle is set at the focal plane of telescopic objective in system, and output end is coupled to IRFPA by coupling lens.
By calibrating the position of each fiber in IRFPA, together with the mapping relationship between input and output of
fiber bundle, a look up table is established. With the table, we can reconstruct the line object image. According to the
scanning period of system, we can get the infrared scanning image.
Image fusion could process and utilize the source images, with complementing different image information, to
achieve the more objective and essential understanding of the identical object. Recently, image fusion has been
extensively applied in many fields such as medical imaging, micro photographic imaging, remote sensing, and computer
vision as well as robot.
There are various methods have been proposed in the past years, such as pyramid decomposition and wavelet
transform algorithm. As for wavelet transform algorithm, due to the virtue of its multi-resolution, wavelet
transform has been applied in image processing successfully. Another advantage of wavelet transform is that it can
be much more easily realized in hardware, because its data format is very simple, so it could save a lot of resources,
besides, to some extent, it can solve the real-time problem of huge-data image fusion. However, as the orthogonal
filter of wavelet transform doesn't have the characteristics of linear phase, the phase distortion will lead to the distortion
of the image edge. To make up for this shortcoming, the biorthogonal wavelet is introduced here. So, a novel image
fusion scheme based on biorthogonal wavelet decomposition is presented in this paper. As for the low-frequency
and high-frequency wavelet decomposition coefficients, the local-area-energy-weighted-coefficient fusion rule is
adopted and different thresholds of low-frequency and high-frequency are set. Based on biorthogonal wavelet
transform and traditional pyramid decomposition algorithm, an MMW image and a visible image are fused in the
experiment. Compared with the traditional pyramid decomposition, the fusion scheme based biorthogonal wavelet
is more capable to retain and pick up image information, and make up the distortion of image edge. So, it has a
wide application potential.