Contour extraction based on improved GVF snake model in ASAR images

This paper proposes an improved GVF Snake-based method which is applied to Envisat ASAR images to determine the interested object´s boundaries. ASAR images have a lot of noise and speckle. But different from other low SNR images, they are also full of texture. While using GVF snake model, the result of the gradient vector field in ASAR images becomes even worse. How to reduce the influence of the unimportant texture and the noise level while to preserve the image features is the key problem. To solve this, log Gabor wavelets that have the ability to preserve the phase data is introduced into the new scheme to correct the gradient vector flow. Results show that the new method can detect the contour of the interested object more accurately and false edges are removed.