3D Image Encoding Based on Dual Tree Complex Wavelets for Plant Phenotyping Precision Agriculture

Authors

  • Bhoomireddy Avinash Reddy  Mtech Student, Department of Ece,Sri Venkateswara College of Engineering, Tirupati, Andhra Pradesh, India
  • Dr. D. Srinivasulu Reddy  Principal, Sv Engineering College for Women, Tirupati, Andhra Pradesh, India

Keywords:

Plant phenotyping, genotype, images compression, 3D data, dual tree wavelets

Abstract

Plant phenotyping is identification of plant appearance and performance with genotype changes and environmental changes the plant is subjected to. As plant phenotyping is multisensory data, and requires huge data base of images compression is vital and hence knowledge on image compression and loss introduced during compression must be addressed during image based plant phenotyping. The proposed research work addresses the most significant image processing technique which is image compression for plant phenotyping. It involves 3D images that are obtained from 2D image data set, plant also has growth pattern which is time dependent. Use of transformational techniques such as wavelets for compression suffers from time shift loss and directionality. As 3D data with time information are directional sensitive, dual tree wavelets are suitable for 3D image compression. Novel algorithms for dual tree based 3D image compressions are explored in this work for plant phenotyping applications.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-06-30

Issue

Volume 3, Issue 5, May-June-2018

Section

Research Articles

License

Copyright (c) IJSRCSEIT

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Bhoomireddy Avinash Reddy, Dr. D. Srinivasulu Reddy, " 3D Image Encoding Based on Dual Tree Complex Wavelets for Plant Phenotyping Precision Agriculture, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 5, pp.1038-1043, May-June-2018.