Edge aware grey image enlargement

Author

Hsieh, Cheng-Hsiung ; Liu, Ching-Hua ; Hung, Wei-Lung ; Zhao, Qiangfu

Author_Institution

Dept. of Comput. Sci. & Inf. Eng., Chaoyang Univ. of Technol., Taichung, Taiwan

fYear

2011

fDate

27-30 Sept. 2011

Firstpage

139

Lastpage

144

Abstract

Interpolation-based approaches for image enlargement generally suffer from the problem of blurry and jagged edge. To deal with the problem, this paper presents an edge aware grey image enlargement approach (EAGIE) which is based on one-dimensional grey polynomial interpolation (1-D GPI). The proposed EAGIE consists of four stages: (i) Canny edge detection, (ii) edge pixel interpolation, (iii) edge adjacent pixel interpolation, and (iv) non-edge pixel interpolation. In the EAGIE, the three groups of pixels are used to find interpolated pixels with the 1-D GPI. The proposed EAGIE is verified and compared with popular 2-D interpolation approaches. Simulation results indicate that the proposed EAGIE has better edge performance than the compared approaches. This suggests the EAGIE is able to relieve the problem of blurry and jagged edge in interpolation-based approaches for image enlargement.

Keywords

edge detection; image resolution; interpolation; polynomials; 1D GPI; 2D interpolation approach; Canny edge detection; EAGIE; blurry edge; edge adjacent pixel interpolation; edge aware grey image enlargement approach; interpolation-based approach; jagged edge; nonedge pixel interpolation; one-dimensional grey polynomial interpolation; Biomedical imaging; Image edge detection; Image resolution; edge aware; edge enhancement; grey polynomial interpolation; image enlargement; image resize;

fLanguage

English

Publisher

ieee

Conference_Titel

Awareness Science and Technology (iCAST), 2011 3rd International Conference on

Conference_Location

Dalian

Print_ISBN

978-1-4577-0887-9

Type

conf

DOI

10.1109/ICAwST.2011.6163128

Filename

6163128