Edge Detection by Sliding Wedgelets

In this paper the sliding wedgelet algorithm is presented together with its application to edge detection. The proposed method combines two theories: image filtering and geometrical edge detection. The algorithm works in the way that an image is filtered by a sliding window of different scales. Within the window the wedgelet is computed by the use of the fast moments-based method. Depending on the difference between two wedgelet parameters the edge is drawn. In effect, edges are detected geometrically and multiscale. The computational complexity of the sliding wedgelet algorithm is O(N2) for an image of size N ×N pixels. The experiments confirmed the effectiveness of the proposed method, also in the application to noisy images.

[1]  F. Friedrich,et al.  Multiscale wedgelet denoising algorithms , 2005, SPIE Optics + Photonics.

[2]  David J. Field,et al.  Emergence of simple-cell receptive field properties by learning a sparse code for natural images , 1996, Nature.

[3]  S. Deans The Radon Transform and Some of Its Applications , 1983 .

[4]  Xiaoming Huo,et al.  Beamlet pyramids: a new form of multiresolution analysis suited for extracting lines, curves, and objects from very noisy image data , 2000, SPIE Optics + Photonics.

[5]  Ronald R. Coifman,et al.  Brushlets: A Tool for Directional Image Analysis and Image Compression , 1997 .

[6]  G. Humphreys Case studies in the neuropsychology of vision , 1999 .

[7]  Wang-Q Lim,et al.  Sparse multidimensional representation using shearlets , 2005, SPIE Optics + Photonics.

[9]  D. Donoho Wedgelets: nearly minimax estimation of edges , 1999 .

[10]  Mohamed S. Kamel,et al.  Image Analysis and Recognition , 2014, Lecture Notes in Computer Science.

[11]  Agnieszka Lisowska Moments-Based Fast Wedgelet Transform , 2010, Journal of Mathematical Imaging and Vision.

[12]  Agnieszka Lisowska Geometrical Multiscale Noise Resistant Method of Edge Detection , 2008, ICIAR.

[13]  Irina Popovici,et al.  Custom-built moments for edge location , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[14]  Stéphane Mallat,et al.  Sparse geometric image representations with bandelets , 2005, IEEE Transactions on Image Processing.

[15]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.