A Non-Local Algorithm for Image Denoising
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
A multi-frame image super-resolution method
Signal Processing
A super-resolution reconstruction algorithm for surveillance images
Signal Processing
Adaptive multiple-frame image super-resolution based on U-curve
IEEE Transactions on Image Processing
A computationally efficient superresolution image reconstruction algorithm
IEEE Transactions on Image Processing
Fast and robust multiframe super resolution
IEEE Transactions on Image Processing
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Super-Resolution (SR) image reconstruction is a technology to reconstruct multiple low-resolution images into one or multiple high-resolution images. As the use of digital camera is recently increasing, the advancement of super-resolution technology gets a great attention. In this study, we propose a regularization-based Super-Resolution algorithm that utilizes an Edge-adaptive Non-Local Means filter. We compare the result of image reconstruction through the algorithm that we proposed and that of image reconstruction through existing studies. As a result, we could verify that a better result would be obtained for regularization function when using an Edge-adaptive Non-Local Means filter rather than using a Non-Local Means filter. We could also obtain much higher PSNR(Peak Signal-to Noise Ratio) than using a Bilateral Total Variation(BTV) method.