Video super resolution method for self-adaption-based superpixel-oriented autoregression model
A superpixel-oriented, autoregressive model technology, applied in the field of computer vision, can solve problems such as image quality needs to be improved, and video cannot be applied
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[0066] The present invention converts super-resolution of low-resolution video into image super-resolution for key frames and non-key frames respectively, wherein the sparse regression method for super-resolution key frames takes less time and has good results, taking video frames into consideration at the same time The spatio-temporal characteristics of non-key frames are super-resolution based on an adaptive superpixel-guided autoregressive model, and finally the super-resolution of video is realized. The obtained results are characterized by rich texture details and higher resolution.
[0067] The video super-resolution method based on the adaptive superpixel-guided autoregressive model of the present invention is characterized in that: video frames are divided into key frames and non-key frames, and a method based on sparse regression and natural image pairs is used for the key frames. The method performs super-resolution, and adopts a method based on an adaptive superpixe...
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