Abstract In compiling a multimedia document we often need to enlarge the size of an image. The traditional pixel repetition method tends to make the edges jagged. On the other hand, the interpolation-based methods tend to make the edges blurry in the enlarging process. In this paper we propose an image magnification method based on a step edge model. Using the model, we are able to define a straight step edge segment with four parameters. In enlarging a digital image, we first derive the parameter values for its step edge segments. This is like extracting the step edges in the corresponding continuous image. Then we re-digitize the step edges in the continuous image with a finer grid to obtain an enlarged image. In this way, the step edges are able to stay well defined after they are enlarged. The experiments show that in both visual comparison and quantitative analysis, the results produced by the suggested step edge model-based approach are consistently and significantly better than that produced by pixel repetition and bilinear interpolation.
[1]
Manfred H. Hueckel.
A Local Visual Operator Which Recognizes Edges and Lines
,
1973,
JACM.
[2]
Jim R. Parker,et al.
Algorithms for image processing and computer vision
,
1996
.
[3]
T. Chen,et al.
Image Decimation and Interpolation Techniques Based on Frequency Domain Analysis
,
1984,
IEEE Trans. Commun..
[4]
Jia-Guu Leu.
Image size reduction and enlargement based on circular apertures
,
1995,
Other Conferences.
[5]
Thomas S. Huang,et al.
Image processing
,
1971
.
[6]
E.E. Pissaloux,et al.
Image Processing
,
1994,
Proceedings. Second Euromicro Workshop on Parallel and Distributed Processing.
[7]
Anil K. Jain.
Fundamentals of Digital Image Processing
,
2018,
Control of Color Imaging Systems.
[8]
H. C. Andrews,et al.
Cubic Splines for image Interpolation and Filtering
,
1978
.