A Study on Fuzzy Wavelet Basis Function for Image Interpolation

다국어 초록 (Multilingual Abstract)

The image interpolation is one of an image preprocessing process to heighten a resolution. The conventional image interpolation used much to concept that it put in other pixel to select the nearest value in a pixel simply, and use much the temporal object interpolation techniques to do the image interpolation by detecting motion in a moving picture presently.
In this paper, it is proposed the image interpolation techniques using the fuzzy wavelet base function. This is applied to embody a correct edge image and a natural image when expand part of the still image by applying the fuzzy wavelet base function coefficient to the conventional B-spline function. And the proposal algorithm in this paper is confirmed to improve about 1.2831 than the image applying the conventional B-spline function through the computer simulation.

목차 (Table of Contents)

• Abstract
• 1. Introduction
• 2. B-Spline Interpolation Function
• 3. Proposed Fuzzy Wavelet Transform
• 4. Simulation and Result
• 5. Conclusions
• References

참고문헌 (Reference)

1 "Wavelet Theory and Its Application to Pattern Recognition" 36 : 2000.

2 "Two-dimensional spline interpolation for image reconstruction" 21 : 275-284, 1988.

3 "Interpolation using Neural Networks for Digital Still Cameras" 46 (46): 610-616, 2000.08

4 "Fast B-spline transforms for continuous image representation and interpolation" 13 : 277-285, 1991

5 "Design of High Speed Weighted FDNN applied DWW Algorithm" 35-c (35-c): 101-108, 1998.07