Two-dimensional wavelet transform de-noising algorithm in collecting intelligent agriculture image

被引：1

作者：

机构：

[1] Harbin University of Science and Technology, Harbin

[2] Jilin Agricultural Science and Technology College, Jinlin

来源：

Chen, D. (yinlaiwu@163.com) | 1600年 / Academy Publisher卷 / 08期

关键词：

2D wavelet transform; Agricultural image collection; De-noising; Wireless sensor;

D O I：

10.4304/jsw.8.4.893-899

中图分类号：

学科分类号：

摘要：

The paper puts forward an image de-noising method based on 2D wavelet transform with the application of the method in agricultural data collection system. As the there are influences of various factors in the collection process through wireless image sensor network, the detail signals of each scale are obtained from multi-scale analysis to replace the original signals with smooth low-frequency signals by applying 2D wavelet transform in de-nosing the images collected. The experiment result shows that the application of 2D wavelet transform image de-noising algorithm can achieve good subjective and objective image quality and help to collect high quality data and analyze the images for the data center with optimum effects. © 2013 ACADEMY PUBLISHER.

引用

页码：893 / 899

页数：6

共 17 条

[1]

Yang S.L., Image Preprocessing and Feature Extraction in Networking Smart Home System, Public Communication of Science & Technology, 23, pp. 233-234, (2011)

[2]

Liang Y.Q., Li Z.M., Sun J., Application of a New Method of Wavelet Image De-noising in Agriculture Picking, Journal of Anhui Agricultural Sciences, 38, 4, pp. 2061-2063, (2010)

[3]

Xun Z.L., Chen Y., Yang G.Q., Zhu X.C., An image thinning Algorithm and its application to agriculture image, Journal of Shandong Agricultural University (Natural Science Edition), 35, 3, pp. 446-450, (2004)

[4]

Liu R.Z., Yan Z.D., Yin W.M., 3D Image Processing Method on Internet of Things, (2011)

[5]

Xiao M.M., Liu Y., On the Automatic Monitoring System of the Networking Crop Pests Image Information, (2011)

[6]

Gai L.P., Tan L.L., Wu J.L., Ding X.D., Chen Y.X., Wang L., Sun F.B., Wang G.L., Two-dimensional wavelet versus wavelet packet technology in de-noising processing at different compression modes, Journal of Clinical Rehabilitative Tissue Engineering Research, 14, 39, pp. 7336-7339, (2010)

[7]

Li J.X., Lin J.H., Yin C.Q., Jin W., Image De-noising in Multi-wavelet Domain Based on Particle Swarm Optimization, Opto-Electronic Engineering, 38, 11, pp. 119-123, (2011)

[8]

Zhao Z.G., Guan C.H., Lv H.X., Non-decimated Wavelet Image Adaptive De-noising with Edge Preservation, Journal of Optoelectronics ·Laser, 18, 11, pp. 1374-1377, (2007)

[9]

Zhao Z.G., Guan C.H., Wavelet image de-noising based on Multi-scale edge detection and adaptive threshold, Chinese Journal of Scientific Instrument, 28, 2, pp. 288-292, (2007)

[10]

Zhou Y., Zhao J.D., Kong M., Image De-noising Based on Wavelet, Journal of West Anhui University, 23, 5, pp. 51-53, (2007)

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