Local area contrast enhancement (LACE) algorithms are employed in thermal imaging applications to improve local contrast in a scene, whereby the image contrast of each region is locally optimized. A potential detriment of this approach is that relative temperature information across the entire image as represented by individual pixel values is lost as a result of the local adjustment of these pixel values necessary to optimize contrast. Thus, objects of the same temperature in different regions of the image may have different pixel values; conversely, objects of different temperatures may appear to have similar pixel values. This loss of relative thermal information can be problematic in certain applications where a need to discriminate objects based on relative temperature exists (e.g. identifying the hot objects in an image). This discrimination ability may be compromised in LACE imagery.
The inherent operation of a LACE algorithm removes information related to the relative temperature difference of pixels across an image. A LACE algorithm adjusts pixel intensity values locally to improve contrast.
As a consequence, the relationship between pixel value and temperature otherwise inherent in thermal imagery is lost. As an example, in a tactical situation it may be necessary to discriminate a vehicle with a running engine (hot) from a vehicle where the engine had been running but had recently been shut off (cooler). In a conventional thermal image, the pixel values corresponding to the hot engine would have a higher display intensity than pixel values associated with the cooler engine. In a LACE enhanced image, the relationship between temperature and pixel intensity is lost. Thus, the higher intensity pixel values may actually represent the cooler engine, since pixel values are adjusted based on the intensity values of their neighbors.
Referring to FIG. 1 illustrating a traditional LACE image, the tree at the far left of the image is slightly whiter (brighter) than the circular image of the sun (right side of image). This would suggest that the tree was in fact higher in temperature than the sun, if this were conventional thermal imagery. Obviously this is not the case, and highlights the effect of LACE in removing relative temperature information from a scene in order to enhance contrast in the image.
This loss of relative temperature information is a fundamental detriment in applications where object discrimination based on temperature is important.
What is needed, therefore, are techniques for preserving relative temperature information in a color augmented LACE-enhanced image.