Agro Image De-Noising (Aid) for Enhanced Agricultural Images
Sangeetha Muthiah1, A. Senthilrajan2
1Aangeetha Muthiah*, Department of Cmputational Logistics, Alagappa University, Karaikudi (Tamil nadu) India.
2Dr. A. Senthilrajan, Department of Cmputational Logistics, Alagappa University, Karaikudi (Tamil nadu) India.
Manuscript received on November 22, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 2474-2478 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B4010129219/2019©BEIESP | DOI: 10.35940/ijeat.B4010.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Several Noises may be present in acquired images. This is an undesired feature for image processing techniques that analyze these images. Image de-noising helps improve efficiency of image processing. Many image de-noising methods have been proposed and exist in literature. Image de-noising methods for agricultural images have been proposed to a lesser extent when compared to the bright medical or photographic images. This paper proposes Agricultural Image De-noising (AID) which uses a discrete wavelet transform (DWT) to eliminate noise in agricultural images. This study uses specific kind of wavelet family spline wavelet transforms with appropriate decomposition level and the wavelet coefficients are analysed with hard and soft threshold methods. The denoised image using various spline wavelets is compared of hard threshold and soft threshold are assessed. The performance of AID is calculated using the peak signal to noise ratio (PSNR) and signal to noise ratio (SNR).
Keywords: Agricultural Image De-noising, DWT, Spline wavele