Title :
Texture enhancement though multiscale mask based on RL fractional differential
Author :
Gan, Zhifeng ; Yang, Hongyu
Author_Institution :
Coll. of Comput. Sci., Sichuan Univ., Chengdu, China
Abstract :
Texture enhancement is one of the most important techniques in digital image processing. In order to enhance the image texture, extract more subtle texture information, and overcome the lack of classical gradient operator, a fractional differential two-dimensional discrete gradient operator based on the definition of RL fractional calculus is extended from one-dimensional operator though analyzing its spectrum. Tow-dimensional isotropic gradient operator mask based on the RL fractional differential was approximately made. The image was implemented through non-linear filter with this mask whose capability of enhancing was increased by controlling the intensity factor. Experimental results show that the operator can extract more subtle information and make the edges more prominent. Compared with the classical Laplacian operator and so on, the proposed method has outstanding promotive effect in texture enhancement.
Keywords :
differential equations; filtering theory; gradient methods; image enhancement; image texture; nonlinear filters; Laplacian operator; RL fractional calculus; RL fractional differential; digital image processing; fractional differential two-dimensional discrete gradient operator; multiscale mask; nonlinear filter; texture enhancement; Automation; Data mining; Image edge detection; Noise; Pixel; fractional differential and integral; fractional differential gradient operator; image enhancement; image processing; texture enhancement;
Conference_Titel :
Information Networking and Automation (ICINA), 2010 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-8104-0
Electronic_ISBN :
978-1-4244-8106-4
DOI :
10.1109/ICINA.2010.5636376