CNN-based WDSR image super-resolution reconstruction optimization method

The invention discloses a CNN-based WDSR image super-resolution reconstruction optimization method. The method comprises the steps of obtaining an original training set and an original test set; constructing an image super-resolution reconstruction model based on a WDSR algorithm, and training the image super-resolution reconstruction model by using the original training set to obtain an initial image super-resolution reconstruction model; optimizing the initial image super-resolution reconstruction model by using an enhanced prediction algorithm to obtain an intermediate image super-resolution reconstruction model; performing reconstruction effect verification on the initial image super-resolution reconstruction model by using the test set; and based on the reconstruction effect verification result, improving the WDSR algorithm until the reconstruction effect verification result meets a preset constraint condition, and obtaining a final image super-resolution reconstruction model. According to the method, on