ITS APPLICATION TO DETECTION OF SMALL OBJECTS IN CORRELATED CLU'I"n:R ·
Pearse A. Ffrencht, Walter H. Kuf · 1994
This paper will focus on the development of an improved 2-D adaptive lattice algorithm (2D-AL) and its application to the removal of correlated clutter to enhance the detectability of small objects in images. The two improvements proposed here are increased flexibility in the calculation of the reflection coefficients and a 2-D method to update the correlations used in the 2D-AL algorithm. The results of the clutter removal will be compared previously published ones for a 2-D LMS (TDLMS) algorithm. 2D-AL is better able to predict spatially varying clutter than the TDLMS algorithm since it converges faster to new image proper ties. Examples of these improvements are shown for a spatially varying 2-D sinusoid in white noise and simulated clouds. The TDLMS and 2D-AL algorithms are also shown to enhance a mammogram image for the detection of small microcalcification s.