Use of constraints in super-resolution of passive millimeter-wave images

This paper discusses the use of constraints when super-resolving passive millimeter wave (PMMW) images. A PMMW imager has good all-weather imaging capability but requires a large collection aperture to obtain adequate spatial resolution due to the diffraction limit and the long wavelengths involved. A typical aperture size for a system operating at 94GHz would be 1m in diameter. This size may be reduced if image restoration techniques are employed. A factor of two in recognition range may be achieved using a linear technique such as a Wiener filter; while a factor of four is available using non-linear techniques. These non-linear restoration methods generate the missing high frequency information above the pass band in band limited images. For this bandwidth extension to generate genuine high frequencies, it is necessary to restore the image subject to constraints. These constraints should be applied directly to the scene content rather than to any noise that might also be present. The merits of the available super-resolution techniques are discussed with particular reference to the Lorentzian method. Attempts are made to explain why the distribution of gradients within an image is Lorentzian by assuming that an image has randomly distributed gradients of random size. Any increase in sharpness of an image frequently results in an increase in the noise present. The effect of noise and image sharpness on the ability of a human observer to recognise an object in the scene is discussed with reference to a recent model of human perception.