A pixel in a particular image has a random brightness, X. The distribution of X depends on whether the pixel belongs to an object (O) of interest or the background (B). If it belongs to the object, then X has a Laplace distribution, fX(x|O) = ? 2 exp(??|x|), ?? < x < ?, where ? = 0.2. If the pixel belongs to the background, then X is uniformly distributed between -10 and 10. Consider the problem of classifying a pixel based on an observation of its brightness, X = x. (a) Find the ML rule for all values of x and illustrate the decision regions on a number line. (b) Find the probability of error if the ML decision rule is used, but the probability that the pixel belongs to the object of interest is equal to 0.6. (c) Adjacent pixels can give information that can be treated as a priori probabilities in determining whether the pixel belongs to the background or the object. If information from adjacent pixels implies that this pixel should belong to the object with probability 3/4, find the MAP decision rule given X = x for all values of x. (d) If information from adjacent pixels implies that this pixel should belong to the object with probability 0.2, find the MAP decision rule given X = x for all values of x.
“I’m trying to write my paper and I’m stuck. Can you help me?”
Yes, we can help you achieve academic success without the uncessary stress of deadlines.
Our reliable essay writing service is a great opportunity for you to save your time and receive the best paper ever.
Find the probability of error
Plagiarism-free and delivered on time!
We are passionate about delivering quality essays.
Our writers know how to write on any topic and subject area while meeting all of your specific requirements.
Unlike most other services, we will do a free revision if you need us to make corrections even after delivery.