arXiv:1309.2057
Single image super resolution in spatial and wavelet domain
원문 초록
Recently single image super resolution is very important research area to generate high resolution image from given low resolution image. Algorithms of single image resolution are mainly based on wavelet domain and spatial domain. Filters support to model the regularity of natural images is exploited in wavelet domain while edges of images get sharp during up sampling in spatial domain. Here single image super resolution algorithm is presented which based on both spatial and wavelet domain and take the advantage of both. Algorithm is iterative and use back projection to minimize reconstruction error. Wavelet based denoising method is also introduced to remove noise.
함께 살펴볼 논문
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IM-LUT: Interpolation Mixing Look-Up Tables for Image Super-Resolution
EAMamba: Efficient All-Around Vision State Space Model for Image Restoration
Structural Similarity-Inspired Unfolding for Lightweight Image Super-Resolution
Plug-and-Play Linear Attention for Pre-trained Image and Video Restoration Models
Grids Often Outperform Implicit Neural Representations
DACN: Dual-Attention Convolutional Network for Hyperspectral Image Super-Resolution
토론
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