Application of Spatial Adaptive Filter in the Tilting Mode of Digital Image Restoration

Abstract:

With the development of computer technology and large scale integrated circuit technology, since 1960s, the development of spatial adaptive filter has become one important part of signal processing, its application field has been extended, especially it is used in the digital image processing, and it has become one of the hot research topics in current. This paper presents the recovery method of introducing spatial adaptive filter in the digital image restoration. Firstly, the spatial adaptive filter theory is described, on the basis of this, the hierarchical modeling equilibrium is proposed in the tilting mode digital image restoration, to carry on the analysis of random signal prediction. At the same time, the hierarchical modeling equilibrium will carry out adaptive weight control based on transverse spatial filtering, to reach image restoration for the right cross point. Finally, this paper carries out in-depth analysis for the realization principle of this method, to provide technology support and practical guidance for the research of this field to a certain extent.

• Periodical: Advanced Materials Research (Volumes 791-793)
• Pages: 1992-1996
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.791-793.1992
• Online since: September 2013
• Authors: Yan Fei Wang
• Keywords: Adaptive Filtering, Image Restoration, MATLAB Software, Modeling Equilibrium, Weight Control

References

[1] Geng Yan, Zhang Duanjin. Summary of adaptive filtering algorithm [J]. Information and electronic engineering, 2010 (04): 102-103.

[2] Gu Mei, Fang Long. Adaptive filtering theory and algorithms [J]. Journal of Anhui electronic information vocational and technical college, 2011 (05): 76-78.

[3] Cui Xutao, He You, Yang Rijie. The simulation and engineering realization of adaptive filtering algorithm [J]. Modern electronic technology, 2011 (18): 34-35.

[4] Tian Lifang. Analysis of time domain adaptive filtering algorithm and the implementation of its MATLAB [J]. Science and technology innovation herald, 2010 (15): 156-157.

[5] Li Yi. Research on the adaptive filtering and filtering algorithm [D]. Northwestern polytechnic university, 2010: 2-11.

[6] Chen Li. Research on the adaptive filtering algorithm and its application [D]. Xi'an electronic and science university, 2010: 1-12.

[7] Liu Zhengjun. MTALAB scientific computing. [M]. Electronic industry press, 2012: 100-115.

[8] Zhou Jianxing. MATLAB from entry to the master [M]. Posts & Telecom Press, 2011: 132-140.

[9] He Zhenya. Adaptive signal processing [M]. Beijing: Beijing science press, 2010: 67-82.

[10] Zou Guoliang. Adaptive filtering theory and application [M]. Hebei University press, 2011: 162-176.

[11] Simon Haykin. Adaptive filter theory [M]. Beijing: Electronic industry press, 2010: 201-211.

[12] M. Tanaka, Y. Kaneda, S. Makino, et al. A fast projection algorithm for adaptive filtering [J]. IEICE trans on fundamentals of electronics, communications and computer sciences, 2011 (10): 1355-1361.

[13] Nurgun E, Filiz S. Wavelet transform based adaptive filter: analysis and new results. IEEE Trans on SP. 2010, 44(9): 263-268.

[14] Treichler, Johnson Jrc, Larimore G. Theory and design of adaptive filters [M]. Johnwiley& Sonslnc, 2011: 112-123.