The invention discloses a method for restoring a motion blurred
image based on a total
variational model and a
neutral network, which mainly solves the problem existing in the prior method that the image cannot be accurately restored. The implementation process comprises the following steps of: (1) constructing a
Toeplitz matrix; (2) working out gradients in
horizontal and vertical directions; (3) initializing the
neutral network; (4) working out a
neuron output; (5) working out the output of the
neutral network; (6) working out a
first variation delta E1 of a network energy function; (7) if the neurons are completely updated,
jumping to the step (4); otherwise,
jumping to a step (8); (8) if the set iterations are reached, outputting a restoration result, otherwise
jumping to a step (9); (9) working out a restoration error; (10) if the restoration error is smaller than the set error, outputting the restoration result, otherwise jumping to a step (11); (11) working out the current input bias matrix; (12) working out a second variation
delta E2 of the network energy function; and (13) if the summation of the
delta E1 and the delta E2 is less than 0, jumping to a step (2); if the summation of the delta E1 and the delta E2 is more than or equal to 0, jumping to the step (3); and if the delta E1 is equal to 0, outputting the restoration result. The method can obtain relatively accurate restored images, and be applied to the restoration of motion blurred images.