Multiwavelets Theory And Application Of Multiwavelets To Image Edge Detection

Distilling image character is based on image edge detection. Image edge has become the important character to pattern recognition, vision of computer, homing etc. And it has been paid more attention, which has broad use.In this paper, three aspect that is theory discussion, algorithms realization and applications are introduced, which aim at edge detection in distilling image character. All kind of methods which are widely used in image edge detection are presented by author. Multiwavelet transform as a new theory is pain lucubration. Algorithms realization for multiwavelet transform, the select of multiwavelet basis, disposing of multiwavelet coefficients are emphases and difficulty for image edge detection based multiwavelet.The theory of multiwavelet is a new theory, whose development is based on scalar wavelet theory. It posses such features as short support, symmetry, orthogonality at the same time, owing more advantages than the scalar ones. By these reasons, multiwavelet transform is widely used in the field of image de-noising, coding and compression. But multiwavelet theory comes out only recently, so the application area is less than scalar wavelet. Especially image edge detection bases on multiwavelet, which is not popular. It applies multiwavelet theory into image edge detection by dig character of multiwavelet coefficients, puts forward three methods of edge detection basing on multiwavelet constant threshold,adaptive threshold and biggest model value. Basing on multiwavelet theory, paper compares its result with other methods, proves that multiwavelet has some advantages on edge detection.