Electro-optic (EO) images exhibit the properties of high resolution and low noise level, while it is a challenge to
distinguish objects with infrared (IR), especially for objects with similar temperatures. In earlier work, we proposed a
novel framework for IR image enhancement based on the information (e.g., edge) from EO images. Our framework
superimposed the detected edges of the EO image with the corresponding transformed IR image. Obviously, this
framework resulted in better resolution IR images that help distinguish objects at night. For our IR image system, we
used the theoretical point spread function (PSF) proposed by Russell C. Hardie et al., which is composed of the
modulation transfer function (MTF) of a uniform detector array and the incoherent optical transfer function (OTF) of
diffraction-limited optics. In addition, we designed an inverse filter based on the proposed PSF to transform the IR image.
In this paper, blending the detected edge of the EO image with the corresponding transformed IR image and the original
IR image is the principal idea for improving the previous framework. This improved framework requires four main steps:
(1) inverse filter-based IR image transformation, (2) image edge detection, (3) images registration, and (4) blending of
the corresponding images. Simulation results show that blended IR images have better quality over the superimposed
images that were generated under the previous framework. Based on the same steps, the simulation result shows a
blended IR image of better quality when only the original IR image is available.