Histograms

Question 1

Histogram equilization is the process that spreads the histogram

Answer 1

False
Histogram equalization is a process that
flattens the histogram

Question 2

The function capable of equalizing the histogram is the probability density function

Answer 2

False
The function 𝑇(𝑟) capable
of equalizing the histogram
is the CDF. Cumilative Distribution Function.

Question 3

T(r) is

-monotonically non
decreasing ?
-The function is bounded ?
-𝑇(𝑟)continuous and non differentiable ?
- inverse is available ?

Answer 3

-monotonically non decreasing ? - True
-The function is bounded ? - True
-𝑇(𝑟)continuous and non differentiable ? - False
- inverse is available ? - True

Cumilative Distribution Function.T(r) is
monotonically non decreasing.

• The function is bounded
  0 ≤𝑇(𝑟) ≤𝐿−1
  0 ≤𝑟≤𝐿−1
• 𝑇(𝑟)continuous and
  differentiable
  The inverse function is
  available

Question 4

Histogram specification: the output shape is flat, but specified by a given function

Answer 4

False
Histogram specification: the output shape is not
flat, but specified by a given function

Question 5

Equalization can be unsuitable when the numberof pixels with low gray levels is very high

Answer 5

True
Equalization can be unsuitable when the numberof pixels with low gray levels is very high

Question 6

Specification function is manually defined

Answer 6

True
Specification function manually
defined