Research of Image Denoising Method about Wavelet Transform with Neighborhood Average

Chen Huang

doi:10.4028/www.scientific.net/AMR.989-994.4054

Paper Titles

Tracking Optimization of FH Signal Based on Wiener Filtering
p.4038

Detection of Nonlinear Frequency Modulated Signal Based on Fractional Fourier Transform
p.4042

Detection of Chirp Signal with Time-Varying Amplitude Based on FRFT
p.4046

Analysis on Ranging and Velocity Measurement Performance of DS/FH Hybrid Spread Spectrum Signal
p.4050

Research of Image Denoising Method about Wavelet Transform with Neighborhood Average
p.4054

Application and Debugging of All-Digital Frequency Synthesizer
p.4058

Electronic Satellite Scheduling Problem and its Heuristic Method
p.4062

Recent Improvements in Image Retrieval
p.4069

Mineral Belt Image Segmentation Using Firefly Algorithm
p.4074

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 989-994Research of Image Denoising Method about Wavelet...

Research of Image Denoising Method about Wavelet Transform with Neighborhood Average

Abstract:

Because wavelet transform has good time-frequency characteristics, and its application in image denoising has been promising. Firstly, use the threshold method of the wavelet transform is used in removing image noise, and then the denoised image is smoothed using neighborhood average filtering with Gauss template. And wavelet denoising process and domain threshold selection principle are discussed. Simulation results show that this method can effectively reduce the noise and can remain most of image details better.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 989-994)

Pages:

4054-4057

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.989-994.4054

Citation:

Cite this paper

Online since:

July 2014

Authors:

Chen Huang*

Keywords:

Image De-Noising, Neighborhood Average Filtering, Wavelet Transform (WT)

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] J Weaver. Filtering noise from images with wavelet transform[J]. Magnetic Resonance in Medicine, 1995, 21, 288-295.

Google Scholar

[2] Selesnick I W, Baraniuk R G, Kingsbury N G. The dual-tree complex wavelet transform[J]. IEEE Trans on Signal Processing, 2005, 22(6): 123-151.

DOI: 10.1109/msp.2005.1550194

Google Scholar

[3] Hu Yaobin, Chen Aihua, Zhang Chunliang Research of denoising technology about wavelet analysis with Wiener filter[J]. Telecommunications for Electric Power System. 2006, 162(27), 42-44.

Google Scholar

[4] Li Zhengfei. Image Noise Reduction Based 0n W avelet Transform[J], MECHAN1CAL ENGINEERING & AUT0MAT10N. 2008, 150(5), 32-34.

Google Scholar

[5] Peiyan Fei, Baolong Guo. Image denoising based on the dyadic wavelet transform[C]. ICCIMA 2003, 9: 402-406.

Google Scholar

[6] Rafael C. Gonzalez. Digital Image Processing[M]. Publishing House of Electronics Industry, (2006).

Google Scholar

[7] Astola J. Fundamentals of nonlinear digital filtering [M]. U.S. A: CRC Press, (1997).

Google Scholar

[8] Le Yang. Image enhancement algorithm and its implementation[J], Modern electronic technology, 2008, 30(8): 133-134.

Google Scholar