Abstract
Electro-optic (EO) image sensors exhibit the properties of high resolution and low noise level at daytime, but they do not work in dark environments. Infrared (IR) image sensors exhibit poor resolution and cannot separate objects with similar temperature. Therefore, we propose a novel framework of IR image enhancement based on the information (e.g., edge) from EO images, which improves the resolution of IR images and helps us distinguish objects at night. Our framework superimposing/blending the edges of the EO image onto the corresponding transformed IR image improves their resolution. In this framework, we adopt the theoretical point spread function (PSF) proposed by Hardie et al. for the IR image, which has the modulation transfer function (MTF) of a uniform detector array and the incoherent optical transfer function (OTF) of diffraction-limited optics. In addition, we design an inverse filter for the proposed PSF and use it for the IR image transformation. The framework requires four main steps: (1) inverse filter-based IR image transformation; (2) EO image edge detection; (3) registration; and (4) blending/superimposing of the obtained image pair. Simulation results show both blended and superimposed IR images, and demonstrate that blended IR images have better quality over the superimposed images. Additionally, based on the same steps, simulation result shows a blended IR image of better quality when only the original IR image is available.
Highlights
Infrared (IR) imaging systems depend on the thermal contrast between objects in the camera view in order to distinguish them
Assuming we have a pair of EO and IR images, four steps are required for this framework: (1) transform the original IR
The following questions will be addressed in this paper: (1) Are there some things we can see that we could not see before by utilizing traditional image fusion methods? (2) Do blended IR images have better quality over the superimposed images? Or vice versa? (3) How do the results look if we use only IR images for processing? Can we derive a similar image with only IR
Summary
Infrared (IR) imaging systems depend on the thermal contrast between objects in the camera view in order to distinguish them. These systems create images by utilizing the infrared energy emitted by the objects as a result of their temperature difference with the background and emissivity Such IR image sensors have low resolution and high noise levels. Assuming we have a pair of EO and IR images, four steps are required for this framework: (1) transform the original IR image into a temperature map via the point spread function (PSF) and design an inverse filter from the literature; (2) detect an edge map of the high resolution EO image; (3) register the transformed IR image and the detected edge map; and (4) blend/superimpose the detected edge map of the EO image with the transformed IR image. In our proposed framework, the edges are detected from EO images, so we could distinguish objects independent of their temperature.
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