Here we are going to apply algorithm analysis to a problem. We are given an image processing algorithm that takes O(n³) time to execute and filter an n by n or (n x n) pixel picture.
It takes 8 seconds for the algorithm to process a 1024 x 1024 pixel picture. How long will it take for the algorithm to process a 1536 x 1536 pixel picture ?
Let’s get right to it and let ‘T’ be a function of time that takes in some input that we will call ‘n’. More specifically ‘T’ is the time that it takes the algorithm to process a n x n pixel, such that we get T(n). For Example:
T(n) is O(n³) according to the statement “we are given an image processing algorithm that takes O(n³) time to execute and filter an n x n pixel picture.” For example:
T(n) = O(n³)
When we say a function is O(n³), what we are stating is that the function grows less than or equal to a constant times n³, such that we get the following:
T(n) ≤ C*n³ whenever n > 0
We can now rewrite our equation to look like the following, since ‘T’ will is less than or equal to C * n³:
T(n) = C* n³
Now according to the problem, the algorithm takes 8 seconds to execute or run when the input size is 1024 x 1024, so we can set up our equation/function and solve for our constant value ‘C’ using this information:
T(1024) = C * (1024)³ = 8 seconds
C = 8 seconds / (1024)³
So our function T(n) = 8 seconds / (1024)³ * n³
Now that we have solved for ‘C’, we can answer the question, “how long will it take for the algorithm to process a 1536 x 1536 pixel picture” by putting the input into the function:
T(n) = 8 seconds / (1024)³ * n³
T(1536) = 8 seconds / (1024)³ * (1536)³
T(1536) =(1536)³/ (1024)³ * 8 seconds
T(1536) =(1536/ 1024)³ * 8 seconds
T(1536) =(3/2)³ * 8 seconds
T(1536) =27/8 * 8 seconds
T(1536) = 27 seconds
Now we know that the time it would take this algorithm to process a 1536 x 1536 pixel picture is no more than 27 seconds.
If you would like to learn more about Algorithm Analysis , you can take my online course here. I also have a course on Udemy.com called Recurrence Relation Made Easy where I help students to understand how to solve recurrence relations and asymptotic terms such as Big-O, Big Omega, and Theta. You can check out my YouTube channel of videos where I solve recurrence relations and perform algorithm analysis on code that anyone can check out for free !
Introduction to Algorithm Analysis [For Complete Beginners]
Understand and solve algorithms using Big O, Big Omega, and Theta time complexity.
Recurrence Relation Made Easy | Udemy
A guide to solving any recursion program, or recurrence relation.
Thanks for reading this article I hope its helpful to you all ! Keep up the learning, and if you would like more computer science, programming and algorithm analysis videos please visit and subscribe to my YouTube channels (randerson112358 & compsci112358 )
Check Out the following for content / videos on Computer Science, Algorithm Analysis, Programming and Logic:
Video Tutorials on Recurrence Relation:
Video Tutorial on Algorithm Analysis: