An Object-oriented Image Smoothing Algorithm Based on the Convexity Model and Multi-scale Segmentation

In image process,smoothing process will effect object edges extraction.In remote sensing image application,it's one of the difficulties to implement smoothing image and ensure the accuracy of edge extraction for specific objects at the same time.In this paper,we propose an object-based and edge-preserve image smoothing algorithm which divides image into many image objects with multi scales by using spatial clustering.In the course of segmentation,all image objects which accord with the Convexity Model will be extracted.Based on the prior object-specified statistical parameters,only those meet the requirements will be smoothed and other ones will be unaffected.Without damaging the edges of specified objects,our method can effectively remove noises and insignificant objects.