Title :
Direction Dependent Decomposition and Edge Detection
Author :
Rajavel, P. ; Aravind, R.
Author_Institution :
Dept. of Electr. Eng., Indian Inst. of Technol., Chennai
Abstract :
This paper presents the multiscale directional decomposition based on the directional frequency information of an image. In general, the pixel values of an image predominantly changes in only a few directions, based on this fact, the directional decomposition is achieved. Two different approaches are used for decomposition namely direction dependent filter bank (DDFB) and multiscale directional Gaussian filter (MDGF). DDFB use the Laplacian pyramid for multiscale decomposition followed by DFB for directional decomposition. MDGF use the Laplacian pyramid for multiscale decomposition followed by directional Gaussian filters for directional decomposition. The number of DDFB subbands at nth stage is 3(2n-2) with a redundancy factor of 4/3. The number of MDFG subbands at nth stage is m(2n-2). This directional dependent decomposition is used for edge detection and results show the better performance compared to several edge detection techniques in the presence of noise.
Keywords :
Gaussian processes; Laplace transforms; edge detection; filtering theory; Laplacian pyramid; direction dependent filter bank; directional frequency information; edge detection; multiscale directional Gaussian filter; multiscale directional decomposition; Data mining; Filter bank; Frequency domain analysis; Image edge detection; Image processing; Image resolution; Laplace equations; Multiresolution analysis; Pixel; Wavelet transforms; Laplacian pyramid; directional Gaussian filter; directional filter bank; edge detection;
Conference_Titel :
Image Processing Theory, Tools and Applications, 2008. IPTA 2008. First Workshops on
Conference_Location :
Sousse
Print_ISBN :
978-1-4244-3321-6
Electronic_ISBN :
978-1-4244-3322-3
DOI :
10.1109/IPTA.2008.4743782