A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Images as Embedded Maps and Minimal Surfaces: Movies, Color, Texture, and Volumetric Medical Images
International Journal of Computer Vision - Special issue on computer vision research at the Technion
Edge Detection with Embedded Confidence
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Review of Nonlinear Diffusion Filtering
SCALE-SPACE '97 Proceedings of the First International Conference on Scale-Space Theory in Computer Vision
Edge Detection and Ridge Detection with Automatic Scale Selection
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
A shearlet approach to edge analysis and detection
IEEE Transactions on Image Processing
The discrete shearlet transform: a new directional transform and compactly supported shearlet frames
IEEE Transactions on Image Processing
The Max Roberts Operator is a Hueckel-Type Edge Detector
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiscale image segmentation by integrated edge and region detection
IEEE Transactions on Image Processing
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Wavelet multi-resolution analysis allows us to detect edges at different scales. However, the wavelet transform can only capture edge information in three directions, horizontal, vertical and diagonal. In addition, the extracted edges are discontinuous. A new edge detection method to solve these problems is proposed in his paper. Firstly, the image is extended symmetrically by applying horizontal and vertical reflections. Secondly, shear transform is taken on the extended images according to various shear matrixes. Thirdly, the edges of the sheared images are detected by means of wavelet transform. The edges detected in different directions have some difference and can complement each other, so we fuse them with a fusion rule. Finally, a threshold is set to refine the edges. The proposed method works efficiently on the images, and the continuity of the edge is getting better. Besides, the method is able to distinguish the real edges from the noise.