Calculation of a binary diffractive optical element to increase the imaging system depth of field in the task of classifying images by a neural network

Using an example of a real-world data set, it is shown that the accuracy of the image classifier based on a convolutional neural network does not deteriorate when using only one color channel. The binary diffractive optical element was calculated, which allows to increase the imaging system depth of field by several times. This is achieved by using the different color channels for various defocus values. A comparison of the MTF curves of the original and apodized imaging systems for a given minimum acceptable value of image contrast is presented.