04-02-2016, 12:58 PM
dt cwt matlab code for image resolution enhancement
ABSTRACT
In this letter, a satellite image resolution enhancement technique based on interpolation of the high-frequency subband images obtained by dual-tree complex wavelet transform (DT-CWT) is proposed. DT-CWT is used to decompose an input low-resolution satellite image into different subbands. Then, the high-frequency subband images and the input image are interpolated, followed by combining all these images to generate a new high-resolution image by using inverse DT-CWT. The resolution enhancement is achieved by using directional selectivity provided by the CWT, where the high-frequency subbands in six different directions contribute to the sharpness of the high-frequency details such as edges. The quantitative peak signal-to-noise ratio (PSNR) and visual results show the superiority of the proposed technique over the conventional bicubic interpolation, wavelet zero padding, and Irani and Peleg based image resolution enhancement techniques.
ABSTRACT
In this letter, a satellite image resolution enhancement technique based on interpolation of the high-frequency subband images obtained by dual-tree complex wavelet transform (DT-CWT) is proposed. DT-CWT is used to decompose an input low-resolution satellite image into different subbands. Then, the high-frequency subband images and the input image are interpolated, followed by combining all these images to generate a new high-resolution image by using inverse DT-CWT. The resolution enhancement is achieved by using directional selectivity provided by the CWT, where the high-frequency subbands in six different directions contribute to the sharpness of the high-frequency details such as edges. The quantitative peak signal-to-noise ratio (PSNR) and visual results show the superiority of the proposed technique over the conventional bicubic interpolation, wavelet zero padding, and Irani and Peleg based image resolution enhancement techniques.