How can I calculate the block-sum of an array?

While going through the area of computer vision, specifically image processing, I came across the concept of “calculating the block-sum” of an array. Can anyone describe what the coined term means? And also provide a code snippet that can be easily interpreted and understood.

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Calculating the block-sum of an array refers to the process of dividing an image into non-overlapping blocks or regions and computing the sum of pixel values within each block. This is a common operation used in computer vision for feature extraction, as it can help to reduce noise and highlight local patterns and structures within an image. The resulting block-sum array can then be used as input for various feature extraction algorithms.

Here is an example code that implements this technique in Python:

  • This code creates a 2D array of size 16x16, and then divides it into non-overlapping blocks of size 4x4 using the np.reshape() function.
  • The np.sum() function is then used to sum over the first and third axes of blocks to obtain the sum of each 4x4 block, which is stored in a new 2D array.