Within the area of image processing, an IR image of a scene comprising one or more objects can be enhanced by combination with image information from a visual image, said combination being known as fusion. A number of technical problems arise when attempting to accomplish such combination and enhancement.
Typically, an imaging device in the form of a camera is provided to capture a visual image and an IR image and to process these images so that they can be displayed together. The combination is advantageous in identifying variations in temperature in an object using IR data from the IR image while at the same time displaying enough data from the visual image to simplify orientation and recognition of objects in the resulting image for a user using the imaging device.
Since the capturing of the IR image and the visual image may be performed by different components of the imaging device, the optical axes between the imaging components may be at a distance from each other and an optical phenomenon known as parallax will arise. To eliminate this and the error arising from an angle between the optical axes, the images must be aligned.
When combining an IR image with a visual image, a number of different methods are known. The most commonly used are known as threshold fusion and picture-in-picture fusion.
In a method for performing a threshold fusion of images, a visual image and an IR image of the same scene are captured. In the IR image, a temperature interval is selected and only those pixels of the image that correspond to temperatures inside the selected interval are chosen and displayed together with information data from all other pixels. The resulting combination image shows the visual image except for those areas where a temperature inside the selected interval can be detected and displays data from the IR image in these pixels instead. For example, when a wet stain on a wall is to be detected, a threshold fusion can be used for determining the extent of the moisture by setting the temperature threshold to an interval around the temperature of the liquid creating the stain. Other parts of the wall will be closer to room temperature and will show up as visual data on a screen, so that the exact position of the stain can be determined. By seeing a texture of the wall, for instance a pattern of a wallpaper, the location of the stain can be further determined in a very precise way.
When performing picture-in-picture fusion, a visual image and an IR image showing the same scene comprising one or more objects are captured, and the pixels inside a predetermined area, often in the form of a square, are displayed from the IR image while the rest of the combined image is shown as visual data. For example, when detecting a deviation in a row of objects that are supposed to have roughly the same temperature, a square can be created around a number of objects and moved until a faulty object is captured besides a correctly functioning one and the difference will be easily spotted. By displaying elements from the visual image outside this square, such as text or pattern, for instance, the precise location of the objects with a specific temperature can be more easily and reliably determined.
The methods for threshold fusion and picture-in-picture fusion all display the chosen section of the combined image as IR data while the rest is shown as visual data. This has the disadvantage that details that are visible in the visual image are lost when showing IR data for the same area. Likewise, temperature data from the IR image cannot be shown together with the shape and texture given by the visual image of the same area.
Some methods exist for blending IR data and visual data in the same image. However, the results are generally difficult to interpret and can be confusing to a user since temperature data from the IR image, displayed as different colors from a palette or different grey scale levels, are blended with color data of the visual image. As a result, the difference between a red object and a hot object, for instance, or a blue object and a cold object, can be impossible to discern. Generally, the radiometric or other IR related aspects of the image, i.e. the significance of the colors from the palette or grey scale levels, are lost when blending the IR image with the visual image.
Thus, there exists a need for an improved way of providing a combined image comprising data from an IR image and data from a visual image together.
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