Wavelet-based super-resolution algorithms for passive millimeter wave imaging

Passive millimeter wave (PMMW) images have inherently the problem of poor resolution due to limited aperture dimension. Thus efficient post-processing is necessary to achieve resolution improvement. In this paper we present a wavelet-based algorithm for resolution enhancement of passive millimeter wave images. In the algorithm, we implement the wavelet-based Landweber iterations as the main image restoration scheme and a wavelet domain Wiener filtering after each five Landweber iteration is completed. A qualitative evaluation of this algorithm is performed with simulated data as well as actual radiometer image captured by 91.5 GHz mechanically scanned radiometer. From experiments, we find that the proposed super-resolution algorithm obtains better results and enhance the resolution and has lower mean square error (MSE).