Noisy Satellite Image Enhancement with wavelet Transforms
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In this book the technique for resolution and contrast enhancement of satellite geographical images based on discrete wavelet transform (DWT), stationary wavelet transform (SWT) and singular value decomposition (SVD) has been proposed. In this, for low resolution and low contrast image, how median filter is used to remove noise is explained. This noiseless low resolution, low contrast image is decomposed into four sub-bands using DWT and SWT. The resolution enhancement is based on the bicubic interpolation of high frequency components obtained by DWT. SWT is used to enhance the input image. Al...
In this book the technique for resolution and contrast enhancement of satellite geographical images based on discrete wavelet transform (DWT), stationary wavelet transform (SWT) and singular value decomposition (SVD) has been proposed. In this, for low resolution and low contrast image, how median filter is used to remove noise is explained. This noiseless low resolution, low contrast image is decomposed into four sub-bands using DWT and SWT. The resolution enhancement is based on the bicubic interpolation of high frequency components obtained by DWT. SWT is used to enhance the input image. All sub-bands are reconstructed as high resolution image by using inverse DWT (IDWT). For contrast enhancement the technique uses DWT and SVD. All sub-bands are reconstructed using IDWT to generate high resolution and high contrast image over conventional techniques. The peak signal-to-noise ratio and root mean square error are then calculated.
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