Resolution-by-resolution improved image super-resolution restoration method based on an attention mechanism
A super-resolution and attention technology, applied in image analysis, image enhancement, image data processing and other directions, can solve problems such as inability to handle multi-scale problems
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[0033] Embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.
[0034] The overall structure of the present invention is as figure 1 shown. A low-resolution image of 480×480 is obtained after downsampling using bicubic linear interpolation. Input low-resolution images into the designed network consisting of convolutional layers and residual blocks to learn the mapping relationship. First, the network model uses a 3×3 deformable convolution for feature extraction of information. The activation unit is RELU, which is used to reduce the interdependence of parameters and solve the occurrence of overfitting problems. Then, four iterative basic block units are designed, and the feature dimensions are 64, 128, and 512 respectively. The block unit is mainly composed of two deformable convolutions and SElayer operations, which can be more conducive to extracting the edge features of the target. Finally, shuffle is use...
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