Frequency separation of a signal in image deblurring tasks

The article discusses how to solve problems with image blur removal by dividing them into high-frequency and low-frequency components, where more emphasis is placed on high-frequency components that represent the majority of blurred images. The effectiveness of various algorithms in eliminating different types of blurring and in conditions of different noise levels is analyzed. The result is a finished image cleaned of various blurring effects using a convolutional neural network and a frequency processing unit.