A novel multiresolution pyramidal edge detector, based on adaptive weighted fuzzy mean(AWFM)filtering and fuzzy linking model, is presented in this paper. The algorithm first constructs a pyramidal structure by repeti...A novel multiresolution pyramidal edge detector, based on adaptive weighted fuzzy mean(AWFM)filtering and fuzzy linking model, is presented in this paper. The algorithm first constructs a pyramidal structure by repetitive AWFM filtering and subsampling of original image. Then it utilizes multiple heuristic linking criteria between the edge nodes of two adjacent levels and considers the linkage as a fuzzy model, which is trained offline. Through this fuzzy linking model, the boundaries detected at coarse resolution are propagated and refined to the bottom level from the coarse-to fine edge detection. The validation experiment results demonstrate that the proposed approach has superior performance compared with standard fixed resolution detector andprevious multiresolution approach, especially in impulse noise environment.展开更多
As a new image analysis technique, Empirical Mode Decomposition （EMD） has been drawn more attention in recent years. In this paper, we proposed a fast EMD method for the edge detection of medical images. We implemen...As a new image analysis technique, Empirical Mode Decomposition （EMD） has been drawn more attention in recent years. In this paper, we proposed a fast EMD method for the edge detection of medical images. We implemented the method in the following steps： a） Decompose the original medical image with the image pyramid technique; b） Implement the EMD at the low resolution level image; c） Map the Intrinsic Mode Functions （IMFs） into the original image; d） Use the edge detector in a coarse IMF at the beginning of the procedure; e） Trace the detected result to the finest IMF to obtain the final image edge. Experimental results demonstrated the effectiveness of the proposed method.展开更多
文摘A novel multiresolution pyramidal edge detector, based on adaptive weighted fuzzy mean(AWFM)filtering and fuzzy linking model, is presented in this paper. The algorithm first constructs a pyramidal structure by repetitive AWFM filtering and subsampling of original image. Then it utilizes multiple heuristic linking criteria between the edge nodes of two adjacent levels and considers the linkage as a fuzzy model, which is trained offline. Through this fuzzy linking model, the boundaries detected at coarse resolution are propagated and refined to the bottom level from the coarse-to fine edge detection. The validation experiment results demonstrate that the proposed approach has superior performance compared with standard fixed resolution detector andprevious multiresolution approach, especially in impulse noise environment.
基金Supported by the National Natural Science Foun-dation of China (60572048)
文摘As a new image analysis technique, Empirical Mode Decomposition （EMD） has been drawn more attention in recent years. In this paper, we proposed a fast EMD method for the edge detection of medical images. We implemented the method in the following steps： a） Decompose the original medical image with the image pyramid technique; b） Implement the EMD at the low resolution level image; c） Map the Intrinsic Mode Functions （IMFs） into the original image; d） Use the edge detector in a coarse IMF at the beginning of the procedure; e） Trace the detected result to the finest IMF to obtain the final image edge. Experimental results demonstrated the effectiveness of the proposed method.
