In this research paper, we propose a new interpolation technique based on the Stationary Wavelet Transform (SWT) and iterative back projection (IBP) for satellite images. Firstly the low resolution image is interpolated by using bicubic interpolation and then decomposed into different subband images...
In this research paper, we propose a new interpolation technique based on the Stationary Wavelet Transform (SWT) and iterative back projection (IBP) for satellite images. Firstly the low resolution image is interpolated by using bicubic interpolation and then decomposed into different subband images by SWT. Each subband is decimated to four lower low resolution images. The four low resolution images are interpolated and registered by using bicubic interpolation and IBP respectively. Inverse SWT (ISWT) is used to generate a Super-resolved output image. The proposed interpolation technique has been tested on several remote sensing images. The quantitative PSNR and SSIM results as well as the visual results show the superiority of the proposed interpolation technique over the other interpolation and image resolution enhancement techniques. For one of the images the PSNR of the proposed method has achieved 3.84dB, 2.11dB, and 1.1dB more improvements than bicubic interpolation, Irani and Peleg technique, and Wavlet Zero Padding technique respectively.
In this research paper, we propose a new interpolation technique based on the Stationary Wavelet Transform (SWT) and iterative back projection (IBP) for satellite images. Firstly the low resolution image is interpolated by using bicubic interpolation and then decomposed into different subband images by SWT. Each subband is decimated to four lower low resolution images. The four low resolution images are interpolated and registered by using bicubic interpolation and IBP respectively. Inverse SWT (ISWT) is used to generate a Super-resolved output image. The proposed interpolation technique has been tested on several remote sensing images. The quantitative PSNR and SSIM results as well as the visual results show the superiority of the proposed interpolation technique over the other interpolation and image resolution enhancement techniques. For one of the images the PSNR of the proposed method has achieved 3.84dB, 2.11dB, and 1.1dB more improvements than bicubic interpolation, Irani and Peleg technique, and Wavlet Zero Padding technique respectively.
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