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Paper Title: SATELLITE IMAGE RESTORATION BASED ON UNIQUE MIXING OF ERLS AND EXTENDED KERNEL DIFFEOMORPHISM FILTER
Authors Name: Priya Lodhi , Prof. Silky Pareyani
Unique Id: IJRTI1810029
Published In: Volume 3 Issue 10, October-2018
Abstract: Satellite images in course of capturing and transmitting are frequently degraded due to channel effects or uncertain conditions. These effects introduce different noise patterns such as, Additive White Gaussian Noise, Salt & Pepper Noise and Mixed Noise. Therefore, retrieved images are highly noise corrupted because the image contents are more attenuated or amplified. The selection of optimum image restoration and filtering technique depends to have knowledge about the characteristics of degrading system and noise pattern in an image. In this thesis, Extended Recursive Least Square (ERLS) adaptive algorithm and kernel diffeomorphism filter (KDF) is used for image restoration from highly noise corrupted images. The implementation of proposed methodology is being carried out by estimating the noise patterns of wireless channel through configuring System Identification with ERLS adaptive algorithm. Then, these estimated noise patterns are eliminated by configuring Signal Enhancement with ERLS algorithm. The restored images are functioned for further denoising and enhancement techniques. The image restoration and further processing algorithms are simulated in MATLAB environment. The performance is evaluated by means of Human Visual System, quantitative measures in terms of MSE, RMSE, SNR & PSNR and by graphical measures. The experimental results demonstrate that RLS adaptive algorithm efficiently eliminated noise from distorted images and delivered a virtuous evaluation without abundant degradation in performance.
Keywords: EKDF: extended Kernel diffeomorphism filter, RLS: Recursive least square, LMS: Least mean square, SNR: Signal to Noise Ratio, AWGN: Additive White Gaussian Noise
Cite Article: "SATELLITE IMAGE RESTORATION BASED ON UNIQUE MIXING OF ERLS AND EXTENDED KERNEL DIFFEOMORPHISM FILTER", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.3, Issue 10, page no.176 - 185, October-2018, Available :http://www.ijrti.org/papers/IJRTI1810029.pdf
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Publication Details: Published Paper ID: IJRTI1810029
Registration ID:180552
Published In: Volume 3 Issue 10, October-2018
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ISSN Number: 2456 - 3315
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