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

Authors(2) :-Bhoomireddy Avinash Reddy, Dr. D. Srinivasulu Reddy

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.

Authors and Affiliations

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

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

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Publication Details

Published in : Volume 3 | Issue 5 | May-June 2018
Date of Publication : 2018-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 1038-1043
Manuscript Number : CSEIT1835243
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Bhoomireddy Avinash Reddy, Dr. D. Srinivasulu Reddy, "3D Image Encoding Based on Dual Tree Complex Wavelets for Plant Phenotyping Precision Agriculture", International 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.
Journal URL : http://ijsrcseit.com/CSEIT1835243

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