Integral image is obtained by summing all the pixels before each pixel (Naively you can think of this as similar to the cumulative distribution function where a particular value is obtained by summing all the values before). Let's take an example to understand this. Suppose we have a 5x5 binary image as shown below. The integral image is shown on the right. [[1, 1, 1, 2, 2], [1, 1, 1, 3, 3], [1, 2, 2, 5, 5], [2, 4, 4, 8, 8], 5, 5, 9, 10]]. [3, Integral image All the pixels in the integral image are obtained by summing all the previous pixels. Previous here means all the pixels above and to the left of that pixel (inclusive of that pixel). For instance, the 3 (blue circle) is obtained by adding that pixel with the above and left pixels in the input image i.e. 1+0+0+1+0+0+0+1 = 3. [[1, 0, 0, 1, 0], [0, 0, 0, 1, 0], [0, 1, 0, 1, 0], [1, 1, 0, 1, 0], [1, 0, 0, 0, 1]] Original image = Write a function integral_image() that takes as parameter an image in the form of a nested list A and returns the integral image.

Integral image is obtained by summing all the pixels before each pixel (Naively you can think of this as similar to the cumulative distribution function where a particular value is obtained by summing all the values before). Let's take an example to understand this. Suppose we have a 5x5 binary image as shown below. The integral image is shown on the right. [[1, 1, 1, 2, 2], [1, 1, 1, 3, 3], [1, 2, 2, 5, 5], [2, 4, 4, 8, 8], 5, 5, 9, 10]]. [3, Integral image All the pixels in the integral image are obtained by summing all the previous pixels. Previous here means all the pixels above and to the left of that pixel (inclusive of that pixel). For instance, the 3 (blue circle) is obtained by adding that pixel with the above and left pixels in the input image i.e. 1+0+0+1+0+0+0+1 = 3. [[1, 0, 0, 1, 0], [0, 0, 0, 1, 0], [0, 1, 0, 1, 0], [1, 1, 0, 1, 0], [1, 0, 0, 0, 1]] Original image = Write a function integral_image() that takes as parameter an image in the form of a nested list A and returns the integral image.

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Question

Integral image is obtained by summing all the pixels before each pixel (Naively
you can think of this as similar to the cumulative distribution function where a
particular value is obtained by summing all the values before). Let's take an
example to understand this.
Suppose we have a 5x5 binary image as shown below. The integral image is
shown on the right.
2,
1, 2, 2],
1, 1, 3, 3],
5, 5],
8],
[1,
2, 2, 5,
[2, 4, 4, 8,
[ 3,
5, 5, 9, 10]].
Integral image
All the pixels in the integral image are obtained by summing all the previous
pixels. Previous here means all the pixels above and to the left of that pixel
(inclusive of that pixel). For instance, the 3 (blue circle) is obtained by adding
that pixel with the above and left pixels in the input image i.e. 1+0+0+1+0+0+0+1
= 3.
[[1, 0, 0, 1, 0],
[0, 0, 0, 1, 0],
[0, 1, 0, 1, 0],
[1, 1, 0, 1, 0],
[1, 0, 0, 0, 1]]
Original image
[[1, 1, 1,
[1,
Write a function integral_image () that takes as parameter an image in the
form of a nested list A and returns the integral image.

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