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This paper presents some results of studies on radar interference rejection using a Hough-Transform-based technique and image processing. If target detection is done by comparing the magnitude of each bin with a threshold produced by a CFAR algorithm, a number of radar systems operating at the same frequency band can cause reciprocal interference, thereby affecting detection and increasing false alarm probability. In this work we will refer to this interference as to "other sensor interference" (OSI). The goal of this work is the definition of methods to detect and remove the interference patterns from radar raw video images. We show that the substitution of interferences with samples estimated from cells (cross range samples) in close proximity of the OSI-affected samples allows CFAR algorithms performance to be improved.