How to determine the number of convolutional operators in CNN?

In computer vision task, such as object classification, with Convolutional Neural Networks (CNN), the network provides an appealing performance. But I'm not sure how to set up the parameters in convolutional layers. For example, a grayscale image (480x480), the first convolutional layer may use a convolutional operator like 11x11x10, where the number 10 means the number of convolutional operators.

The question is how to determine the number of convolutional operators in CNN?

You're going to be doing: $10 + 20 + 100 = 130$ multi channel 2D convolutions each with a depth of 1, 10, and 20 respectively. As you can see, the depth of each convolution is going to change as a function of the depth of the input volume from the previous layer.
But I assumed that you're trying to figure out how to compare this to a single channel 2D convolution. Well, you could just multiply the depth of each input volume by the number of filters in each layer and add them together. In your case: $10 + 200 + 2000 = 2,210$.