Review of super-resolution techniques for passive millimeter-wave imaging

This paper reviews the mathematical image processing methods available for super-resolving passive millimeter wave (PMMW) images. PMMW imaging has a number of advantages over infra-red (IR) and visible imaging in being able to operate under adverse weather conditions making it useful for all weather surveillance. The main disadvantage, however, is the size of aperture required to obtain usable spatial resolution. A typical aperture size would be 1m diameter for a system operating at 94GHz. This aperture may be reduced if super-resolution techniques are employed. To achieve super-resolution non-linear methods of restoration are required in order to generate missing high frequency information. For these to be genuine high frequencies it is necessary to restore the image subject to constraints. These constraints should apply directly to the scene content rather than to properties of any noise also present. The merits of the available super-resolution techniques are discussed with reference to sharpening noisy PMMW images. Any increase in sharpness of an image frequently results in an increase in the noise present. This can detract from the ability of a human observer to recognise an object in the scene. This problem is discussed with reference to a recent model of human perception.