scholarly journals Satellite Image Enhancement Using Dual Tree Complex Wavelet Transform

2017 ◽  
Vol 6 (4) ◽  
pp. 334-336
Author(s):  
C. Periyasamy
Keyword(s):  
Wavelet Transform ◽  
High Frequency ◽  
Signal To Noise Ratio ◽  
Satellite Image ◽  
Resolution Enhancement ◽  
Intermediate Stage ◽  
Image Resolution ◽  
Complex Wavelet Transform ◽  
Enhancement Technique ◽  
Complex Wavelet

Drawback of losing high frequency components suffers the resolution enhancement. In this project, wavelet domain based image resolution enhancement technique using Dual Tree Complex Wavelet Transform (DT-CWT) is proposed for resolution enhancement of the satellite images. Input images are decomposed by using DT-CWT in this proposed enhancement technique. Inverse DT-CWT is used to generate a new resolution enhanced image from the interpolation of high-frequency sub band images and the input low-resolution image. Intermediate stage has been proposed for estimating the high frequency sub bands to achieve a sharper image. It has been tested on benchmark images from public database. Peak Signal-To-Noise Ratio (PSNR) and visual results show the dominance of the proposed technique over the predictable and state-of-art image resolution enhancement techniques.

Satellite Image Enhancement Using Dual Tree M-Band Wavelet Transform

2017 ◽  
Vol 8 (3) ◽  
pp. 737
Author(s):  
C. Periyasamy
Keyword(s):  
Wavelet Transform ◽  
High Frequency ◽  
Signal To Noise Ratio ◽  
Satellite Image ◽  
Resolution Enhancement ◽  
Intermediate Stage ◽  
Image Resolution ◽  
Enhancement Technique ◽  
Frequency Components ◽  
Visual Results

<p>Drawback of losing high frequency components suffers the resolution enhancement.  In this project, wavelet domain based image resolution enhancement technique using Dual Tree M-Band Wavelet Transform (DTMBWT) is proposed for resolution enhancement of the satellite images. Input images are decomposed by using DTMBWT in this proposed enhancement technique. Inverse DTMBWT is used to generate a new resolution enhanced image from the interpolation of high-frequency sub band images and the input low-resolution image. Intermediate stage has been proposed for estimating the high frequency sub bands to achieve a sharper image. It has been tested on benchmark images from public database. Peak Signal-To-Noise Ratio (PSNR) and visual results show the dominance of the proposed technique over the predictable and state-of-art image resolution enhancement techniques.</p>

scholarly journals Image Resolution Enhancement Using Transform

2018 ◽  
Vol 9 (2) ◽  
pp. 354
Author(s):  
Syed Nazeeburrehman ◽  
Mohameed Ali Hussain
Keyword(s):  
High Frequency ◽  
Signal To Noise Ratio ◽  
Resolution Enhancement ◽  
Intermediate Stage ◽  
Image Resolution ◽  
Discrete Wavelet ◽  
Public Database ◽  
Enhancement Technique ◽  
Visual Results ◽  
State Of Art

In this project, interruption based image resolution enhancement technique using Discrete Wavelet Transform (DWT) with high-frequency sub bands obtained is proposed. Input images are decomposed by using DWT in this proposed enhancement technique. Inverse DWT is used to generate a new resolution enhanced image from the interpolation of high-frequency sub band images and the input low-resolution image. Intermediate stage has been proposed for estimating the high frequency sub bands to achieve a sharper image. It has been tested on benchmark images from public database. Peak Signal-To-Noise Ratio (PSNR) and visual results show the dominance of the proposed technique over the predictable and state-of-art image resolution enhancement techniques.

Dual-tree complex wavelet transform and SVD based medical image resolution enhancement

2014 ◽  
Vol 105 ◽  
pp. 430-437 ◽  
Author(s):  
Muhammad Zafar Iqbal ◽  
Abdul Ghafoor ◽  
Adil Masood Siddiqui ◽  
Muhammad Mohsin Riaz ◽  
Umar Khalid
Keyword(s):  
Wavelet Transform ◽  
Medical Image ◽  
Resolution Enhancement ◽  
Image Resolution ◽  
Complex Wavelet Transform ◽  
Complex Wavelet

Infrared and visible image fusion using dual-tree complex wavelet transform and convolutional sparse representation

2020 ◽  
Vol 39 (3) ◽  
pp. 4617-4629
Author(s):  
Chengrui Gao ◽  
Feiqiang Liu ◽  
Hua Yan
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
Sparse Representation ◽  
High Frequency ◽  
Low Frequency ◽  
Infrared Images ◽  
Complex Wavelet Transform ◽  
Visible Image ◽  
Visible Images ◽  
Complex Wavelet

Infrared and visible image fusion refers to the technology that merges the visual details of visible images and thermal feature information of infrared images; it has been extensively adopted in numerous image processing fields. In this study, a dual-tree complex wavelet transform (DTCWT) and convolutional sparse representation (CSR)-based image fusion method was proposed. In the proposed method, the infrared images and visible images were first decomposed by dual-tree complex wavelet transform to characterize their high-frequency bands and low-frequency band. Subsequently, the high-frequency bands were enhanced by guided filtering (GF), while the low-frequency band was merged through convolutional sparse representation and choose-max strategy. Lastly, the fused images were reconstructed by inverse DTCWT. In the experiment, the objective and subjective comparisons with other typical methods proved the advantage of the proposed method. To be specific, the results achieved using the proposed method were more consistent with the human vision system and contained more texture detail information.

Sign in / Sign up

Export Citation Format

Share Document