Optimized Wavelet Decomposition and Gaussian interpolation based Satellite Image Enhancement
T. V. Hyma Lakshmi1, K. Ch. Sri Kavya2, T. Madhu3, K. Sarat Kumar4

1T.V. Hyma Lakshmi*, Pursuing Ph.D, Koneru Lakshmaia Education Foundation, Guntur, Andhra Pradesh, India.
2Dr. K. Ch. Sri Kavya, Professor, Department of Electronics and Communication Engineering, KLEF. Guntur, Andhra Pradesh, India.
3Dr. Tenneti Madhu, Principal, Bhimavaram, Andhra Pradesh, India.
4Dr. K. Sarat Kumar, Professor, Department of E.C.E., KLEF, Guntur, India
Manuscript received on January 12, 2020. | Revised Manuscript received on January 22, 2020. | Manuscript published on February 10, 2020. | PP: 2609-2612 | Volume-9 Issue-4, February 2020. | Retrieval Number: D2056029420/2020©BEIESP | DOI: 10.35940/ijitee.D2056.029420
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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: Satellite images (SI) play a vital role in various remote sensing applications like geoscience, geographical studies, observing the earth’s atmosphere, monitoring natural disasters, etc. The SI are used in these applications require high-resolution. The performance of the wavelet transforms based resolution enhancement methods depends on the type of the mother wavelet used and it varies with image to image. The novel robust SI resolution enhancement technique including Optimized wavelet transform based image decomposition and Gaussian interpolation is proposed in this paper. Optimized wavelet decomposition is obtained using the Stochastic Diffusion Search algorithm and the Gaussian distribution function is used for interpolation. The proposed method is compared with the Discrete wavelet decomposition and Gaussian interpolation resolution enhancement method and proved that the proposed method gives the best results for any image. 
Keywords: Bicubic Interpolation, Discrete Wavelet Transform, Optimized Wavelet Transform, PSNR, UIQI.
Scope of the Article:  Discrete Optimization