Most image's interpreters are concerned with recognizing linear features in images. For geological
purposes, faults, joints, features, dykes and geological contacts are the main linear features which must
be interpreted. The linear features are formed by edges, where some edges are marked by pronounced
differences in brightness and become ready recognized. This paper deals with satellite image edge
detection techniques. Edge detection is the name for a set of mathematical methods which aim at
identifying points in a satellite image at which the image brightness changes sharply or, more formally,
has discontinuities. These points are typically organized into a set of curved line segments termed edges.
Important features can be extracted from the edges of an image (e.g., corners, geological boundary, linesand
curves). In this paper, a novel edge detection technique which computes edges of satellite image using two
dimensional (2D) design digital filter is presented and applied on Gabal Gattar granitic batholith to enhance
boundaries between granite and surrounded rocks in one hand, and between the granitic phases on another
hand, as well as, enhance the shape of granitic masses, and faults, dykes, fractures cutting them. Here the
proposed methodology is compared with other edge detectors. Filters (Sobel, Roberts, Prewitt, Canny
and Log filters) as applied on G. Gattar granitic mass. This study reveals that the new proposed (Raafat
filter) porttery the contacts and linear features more obvious than the other operators.