aula_02

Question 1

What are the 2 types of low level image processing?

Answer 1

-Arithmetic operations
-Pixel relations

Question 2

What kind of Arithmetic operations are there?

Answer 2

– Addition
– Substraction
– Multiplication
– Division
as well as logical operations like :
AND, OR, NOT, …..

Question 3

What many image processing operations make use ?

Answer 3

Of spatial relationships between pixels.
A number of methods have been devised to specify pixel
neighbours and calculate distance.
* The 4-neighbours of a pixel (x,y) are the closest pixels in
horizontal and vertical directions (D4) - like a cross
* The 8-neighbors are the 4-neighbors plus the four
closest pixels in diagonal direction (D8) - all the neighbours

Question 4

How do we calculate the pixel distance?

Answer 4

it can be calculated with the euclidean way but the sqrt makes it expensive to calculate, despite being the most accurate
–Euclidean (L2): 𝐷 = sqrt([(𝑥 − 𝑢) 2 + (𝑦 − 𝑣) 2 ])
– City-block (L1): D = |𝑥 − 𝑢| +| 𝑦 − 𝑣|
– Chessboard (Linf): D = max (|𝑥 − 𝑢| ,| 𝑦 − 𝑣|)

Question 5

What is intensity level slicing?

Answer 5

It means highlighting a specific range of
intensities in an image.

Question 6

Is threshold a specific case of intensity level slicing?

Answer 6

Yes.

Question 7

What types of threshold there are?

Answer 7

There are:
-Threshold binary
-Threshold binary
-Threshold binary
-Threshold binary

Question 8

How many types of threshold there are?

Answer 8

There are 5 types:
-Threshold binary
-Threshold binary, inverted
-Truncate
-Threshold to zero
-Threshold to zero, inverted

Question 9

What is threshold binary?

Answer 9

it corresponds to the maxval accepted ( normally 1) if the value of the function src(x,y) is > tresh value, and it is 0 otherwise

Question 10

What is threshold binary inverted?

Answer 10

It is the same as threshold binary but it is 0 if the value of the function src(x,y) is > tresh value and it is 1 or max value otherwise

Question 11

What is Truncate?

Answer 11

If the function value is > thresh value, it truncates it to the thresh value, otherwise it is the value of the function itself src(x,y)

Question 12

What is Threshold to Zero?

Answer 12

It is src(x,y) if the function > the thresh value and it is 0 otherwise

Question 13

What is Threshold to Zero, Inverted?

Answer 13

It is src(x,y) if the function < the thresh value and it is 0 otherwise ( if the src(x,y) > thresh value)

Question 14

What is an histogram? What they allow us to see?

Answer 14

• An histogram is a graphical display of
  tabulated frequencies.
• Typically represented as a bar chart
  *histograms allow us to see the colour
  or intensity distribution

Question 15

Wow can the collected counts of data be organized
in a histogram?

Answer 15

Into a set of predefined bins.

Question 16

What are the three important parts of the histograms?

Answer 16

Important parts of an histogram:
– dims: The number of parameters you want to collect data.
– bins: The number of subdivisions in each dim.
– range: The limits for the values to be measured.

Question 17

What are the two parts of the Operation based on histogram

Answer 17

– Determination and analysis of histogram
– Image improvement based on the histogram.

Question 18

How is an histogram ideal distributed?

Answer 18

An ideal histogram is evenly
distributed, edge to edge,
not up the sides.

Question 19

And a histogram for a dark
subject?

Answer 19

it is just more shifted to the left to
represent the tones of the
subject. It is not wrong

Question 20

And a histogram for a light
subject (e.g., a white cat)?

Answer 20

Since it mostly has light tones in the scene
and few dark areas, it is shifted to the right compared
to the dark subject

Question 21

And how can it be a graph for a overexposed image?

Answer 21

The gap on the left side of the graph indicates there a lack of blacks in the image.
It also means you will lose lots of detail in the white areas
that may not be recoverable. In this case, shift
to give your image less exposure and shoot
the scene again.

Question 22

And if the opposite happens? How do you call it?

Answer 22

This histogram shows the opposite. Now we see a gap on the
right side of the graph indicating there are no whites
represented, so the image will be dark – too dark. You can
safely give the image more exposure until you see the tones
just touch the right edge of the histogram.
It is called Underexposed

Question 23

Again, what defines an underexposed image? (exposition)

Answer 23

Loss of details in dark areas

Question 24

Again, what defines an overexposed image? (exposition)

Answer 24

Loss of details in bright areas

Question 25

Histograms can also have different intensity levels? (intensity)

Answer 25

Yes, for example: 256, 64 and 6 intensity levels

Question 26

And how is contrast defined? (contrast)

Answer 26

Contrast is defined as the difference in intensity between two objects in an image. If the contrast is too low, it is impossible to distinguish between two objects, and they are seen as a single object. A lot of zones that dont have values, whereas in other zones there are very high values

Question 27

Can the contrast be manipulated? (contrast)

Answer 27

Yes.
Using for example contrast stretching and also histogram equalization (extension of contrast stretching)

Question 28

How does the histogram equalization occurs?

Answer 28

-It is analysed by a function T(z) to reshape
the image to make its histogram flat and wide.
– A typical solution is to use the cumulative histogram
(integral of intensity histogram) as the intensity
mapping function.

Question 29

Are there also color histograms?

Answer 29

Yes. They have a histogram for each of the colors (RGB for example)

Question 30

What is image smoothing or blurring? (filtering)

Answer 30

It is also known as neighbourhood averaging:
– Used to remove noise or a pre-processing for edge
detection
– Filtering operation in which a weighted array is
moved over the original image while computing the
pixel as a weighted average:

Question 31

Can it use different filters/kernels?

Answer 31

Yes.
For each pixel there is aplied a operation that allows a kernel to modify the value of the pixel itself and its neighbours

Question 32

And how does it work on the borders?

Answer 32

Since it has no neighbours in the corners/borders, the kernel can aplly different values, like for example:
- constant value;
- value of the closest border;
- mirror at the image boundary;
- periodically repeat along axis

Question 33

And what is the average filter for noise reduction?

Answer 33

– It is Kind of the low pass filter, the larger the size, the
larger the cut-off frequency.
– This is an approximation since smoothing operation
is performed in space and not in frequency domain.

Question 34

What examples of linear filter are there?

Answer 34

-The box filter with nine neighbours with 1 value and the outsider neighbours with 0
-The gaussian filter that has 9 in the pixel, 5 in the vertical and horizontal neighbours and then starts to decrease
-The “Laplace” or “Mexican Hat” filter that has 16 value in the pixel and then negatives around and 0 in the outsider neighbours

Question 35

And does the median filter works?

Answer 35

It apllies a sorting of the pixels values and then ????

Question 36

And is there any other version of the median filter?

Answer 36

Yes, a weighted median filter that weight the sorted pixel values

Question 37

How do geometrical transformations essentiatly occur?

Answer 37

The Value of image I at original location (x,y)
moves to new position (x′,y′) in transformed
image I′ based on a geometric mapping T

Question 38

And what kind of geometrical transformations can be applied?

Answer 38

There are Linear (Afiine and Projective) and Non linear types

Question 39

Which ones are Linear?

Answer 39

In the Affine group:
– Translation, rotation, and scaling (contract and stretch) which does not preserve lines and parallelism
In the Projective:
– It is a Particular case of affine which does not preserve parralelism

Question 40

Which ones are Non Linear?

Answer 40

For example the :
-twirl, ripple, sphere, …

Question 41

And what are the Geometrical transformations used for?

Answer 41

They are used for example:
– Correction of distortion (Camera lens correction)
– Texture mapping (Computer Graphics)
– Morphing (Special effects in movies)