An Iterative Super-Resolution Reconstruction of Image Sequences using Fast Affine Block-Based Registration with BTV Regularization

Author(s):  
V. Patanavijit ◽  
S. Jitapunkul
2014 ◽  
Vol 610 ◽  
pp. 425-428
Author(s):  
Wei Jian Liu ◽  
Si Da Xiao ◽  
Ruo He Yao

In this paper, we propose a new super-resolution algorithm based on wavelet coefficient. The proposed algorithm uses discrete wavelet transform (DWT) to decompose the input low-resolution image sequences into four subband images, including LL, LH, HL, HH. Then the input images have been processed by the 3DSKR (Three Dimensional Steering Kernel Regression) super resolution (SR) algorithm, and the result replaces the LL subband image, while the three high-frequency subband images have been interpolated. Finally, combining all these images to generate a new high-resolution image by using inverse DWT. Proposed method has been verified on Calendar and Foliage by Matlab software platform. The peak signal-to-noise (PSNR), structural similarity (SSIM) and visual results are compared, and show that the computational complexity of the proposed algorithm decline by 30 percent compared with the existing algorithm to obtain the approximate results.


Author(s):  
Jieping Xu ◽  
Yonghui Liang ◽  
Jin Liu ◽  
Zongfu Huang ◽  
Xuewen Liu

Author(s):  
Xiong Zhang ◽  
Congli Feng ◽  
Anhong Wang ◽  
Linlin Yang ◽  
Yawen Hao

2013 ◽  
Vol 23 (5) ◽  
pp. 1451-1462 ◽  
Author(s):  
Sara Izadpanahi ◽  
Hasan Demirel

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