An algorithm for contrast enhancement and segmentation of complex geophysical images

Image segmentation is one of the most important steps leading to the analysis of processed image data; its main goal is to divide an image into parts that have a strong correlation with objects or areas of the real world contained in the image. We present a segmentation method which uses deformable models from a very complex image (with layers, faults...) having homogeneous grey levels. We first give a method to improve the contrast of the image before proposing a method to segment the obtained image. The originality of this segmentation method is that we have interpolation data and triple (and quadruple!) points that involve making some geometric constraints on the model. Numerical results are given.