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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
This book covers the contents of my Ph.D work. The despeckling concept of synthetic aperture radar (SAR) imagery and object recognition and classification of the SAR imagery dataset has been covered. The various available literature with their pros and cons and tried to overcome them with a new approach by utilizing some optimization methods has been explained. The SAR image despeckling process has been covered by introducing a new framework in which I have applied a fruit fly optimization algorithm to enhance the execution time and also improved the smoothness of the images without losing any image information. Different machine learning algorithms have been used to compare the classification result based on original SAR imagery and despeckled SAR imagery. Experimental results depict found the improved performance in terms of different parameters.
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
This book covers the contents of my Ph.D work. The despeckling concept of synthetic aperture radar (SAR) imagery and object recognition and classification of the SAR imagery dataset has been covered. The various available literature with their pros and cons and tried to overcome them with a new approach by utilizing some optimization methods has been explained. The SAR image despeckling process has been covered by introducing a new framework in which I have applied a fruit fly optimization algorithm to enhance the execution time and also improved the smoothness of the images without losing any image information. Different machine learning algorithms have been used to compare the classification result based on original SAR imagery and despeckled SAR imagery. Experimental results depict found the improved performance in terms of different parameters.