A method for generating an image processing filter includes: adjusting; and extracting. The adjusting inputs first training image data into a neural network to generate output image data, calculates an evaluation value based on a loss function using the output image data and second training image data, and adjusts a convolution filter so as to reduce the evaluation value. The extracting extracts data from the adjusted convolution filter as data for the image processing filter. A first training image includes noise and reproduces a test pattern. A second training image includes reduced noise and reproduces the test pattern. The loss function includes a first term and a second term. The first term specifies a magnitude of a difference between the output image data and the second training image data. The second term grows smaller as symmetry of the convolution filter relative to a filter axis of symmetry increases.