Answer:
Explanation:
In digital image processing, degradation is a process of introducing defects to the image. Understanding the degradation function will allow restoration of the original image.
There are many different causes for image degradation such as motion blur, digital noise and lens off-focus. In cases like motion blur, it is possible to come up with an very good estimate of the actual blurring function and "undo" the blur to restore the original image. For digital noise, a statistical model can be set up to compensate for the degradation it caused. Similarly lens focus can be compensate by an optical model if the mis-focus is known.
The above are three degradations that I could find. A lot more information can be found about restoration functions. If you search for image degradation online, you will find a discussion on Quora and an interesting introduction from Rice University. Good luck!
I don’t understand how this question can u explains more or be a little more specific please.
Answer:
Written in Python
import math
principal = 8000
rate = 0.025
for i in range(1, 11):
amount = principal + principal * rate
principal = amount
print("Year "+str(i)+": "+str(round(amount,2)))
Explanation:
This line imports math library
import math
This line initializes principal amount to 8000
principal = 8000
This line initializes rate to 0.025
rate = 0.025
The following is an iteration from year 1 to 10
for i in range(1, 11):
This calculates the amount at the end of the year
amount = principal + principal * rate
This calculates the amount at the beginning of the next year
principal = amount
This prints the calculated amount
print("Year "+str(i)+": "+str(round(amount,2)))
All parts of a statement must be true for it to be true
