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Sensors 2017, 17(1), 142;

Nonlinear Fusion of Multispectral Citrus Fruit Image Data with Information Contents

School of Engineering, University of South Australia, Mawson Lakes 5095, Australia
Department of Electronics Engineering, Incheon National University, 119 Academy Road, Yeon Su Gu, Incheon 22012, Korea
Author to whom correspondence should be addressed.
Academic Editor: Gonzalo Pajares Martinsanz
Received: 6 November 2016 / Revised: 27 December 2016 / Accepted: 9 January 2017 / Published: 13 January 2017
(This article belongs to the Collection Sensors in Agriculture and Forestry)
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The main issue of vison-based automatic harvesting manipulators is the difficulty in the correct fruit identification in the images under natural lighting conditions. Mostly, the solution has been based on a linear combination of color components in the multispectral images. However, the results have not reached a satisfactory level. To overcome this issue, this paper proposes a robust nonlinear fusion method to augment the original color image with the synchronized near infrared image. The two images are fused with Daubechies wavelet transform (DWT) in a multiscale decomposition approach. With DWT, the background noises are reduced and the necessary image features are enhanced by fusing the color contrast of the color components and the homogeneity of the near infrared (NIR) component. The resulting fused color image is classified with a C-means algorithm for reconstruction. The performance of the proposed approach is evaluated with the statistical F measure in comparison to some existing methods using linear combinations of color components. The results show that the fusion of information in different spectral components has the advantage of enhancing the image quality, therefore improving the classification accuracy in citrus fruit identification in natural lighting conditions. View Full-Text
Keywords: image fusion; entropy filter; multiscale decomposition; wavelet transform; clustering image fusion; entropy filter; multiscale decomposition; wavelet transform; clustering

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Li, P.; Lee, S.-H.; Hsu, H.-Y.; Park, J.-S. Nonlinear Fusion of Multispectral Citrus Fruit Image Data with Information Contents. Sensors 2017, 17, 142.

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