Image Processing and Analysis Flashcards

1
Q

Image processing:

Image in =

A

Image out

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Image analysis:

Image in =

A

Data out

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

3 major steps in the history of digital imaging?

A
  1. Capturing images
  2. Transmission of images
  3. Computer graphics and digital images
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

What is a pixel? How does this relate to resolution?

A

PICture ELement - discrete, smallest unit of a picture. More pixels = greater resolution.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

What 3 things determine pixel size?

A
  1. Lens
  2. Optical path
  3. Sensor
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

8 bits provide ____ possible grey levels.

A

256

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

How many discrete shades of grey can the human eye detect? How does this impact on the minimum bit number per pixel?

A

50 discrete shades - there pixels should have a minimum of 6-7 bits each so that the human eye sees colour change as a seamless transition.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

How does resolution influence image size and storage capacity?

A

The higher the resolution of the image, the more data points there are (the bigger the image), the more storage capacity you will need on your hard drive.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

What are 3 image fomats designed for web (compressed)?

A
  1. Portable Network Graphics (PNG)
  2. GIF - max of 256 colours
  3. Joint Photographic Experts Group (JPEG)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

What are 3 image fomats designed for the professional (uncompressed)?

A
  1. Photoshop’s Native Format (PNF)
  2. Tagged Image Format (TIFF)
  3. Window’s bitmap (BMP)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

When manipulating an image, what should you not exceed?

A

An acceptable scientific standard in modification of images

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Define CONTRAST

A

The difference in absolute or perceived intensity between an object and its surroundings. Assign darkest pixel to black (0) and lightest pixel to white (1).

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

What is SHARPENING? How does it help the viewer?

A

Produces an increase in local contrast at boundaries. This has the effect of making edges easier for the viewer to see, consequently making the boundaries appear sharper.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

What is SMOOTHING? Why is it done and what is a negative consequence of this?

A

Aim to reduce random noise.
Assumes all pixels belong to the same structure (at edges this is not true) and as a result, smoothing filters might cause blurring or shifting of edges, which is undesirable.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Image data sets can be: 2-D ( _ and _ ), 3-D ( _, _ & _ ) and 4-D ( _, _, _ & _).

A

2D - (X and Y)
3D - (X, Y and Z)
4D - (X, Y, Z & t)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

What are 2 places that images can be stored?

A
  1. laboratory information management system (LIMS)

2. Online server

17
Q

Why should you not use JPEG when conducting image analysis?

A

JPEG is a compressed file and therefore it has decreased resolution (which isn’t good for image analysis).

18
Q

What is LOSSY COMPRESSION and why is it not good in Science?

A

It compresses the image but permanently discards the unretained information. Happens through the process of INTERPOLATION. Therefore can’t go back. In Science we need to retain the raw image. Often software with filters will undergo Lossy Compression.

19
Q

Define IMAGE ANALYSIS.

A

The science of measuring size and shape of objects through imaging using mathematical procedures.

20
Q

Most image analysis software is expensive. What is a gold standard program that is free?

A

ImageJ/FIJI

21
Q

What are 5 characteristics of Image J?

A
  1. Can read many image formats
  2. Can calculate area and pixel value statistics
  3. Can measure distances and angles
  4. All of this can be done at any magnification factor
  5. Supports a stack of images in one single window
22
Q

What is MORPHOMETRICS?

A

A quantitative analysis of form. This includes: size, shape, area, surface area, distance, length, mean diameter, perimeter.

23
Q

Formulas are used to work out the SA of regular shapes. How is the SA of irregular shapes determined? Perimeter?

A

SA: counting the number of pixels it comprises.
P: counting the pixels that touch the background or by manually tracing

24
Q

What is the MAJOR AXIS?

A

Longest line that can be drawn through the object. Done by counting the number of pixels.

25
Q

What is the MINOR AXIS?

A

Perpendicular to major axis (it is the width).

26
Q

What is the ASPECT RATIO?

A

height/width = major axis/minor axis

27
Q

What is FORM FACTOR and what formula is used to calculate it?

A

A.K.A. compactness. Depends on object’s shape but not dimensions. FF = (4π area) / (perimeter ^2)

28
Q

Define FIBRE LENGTH and FIBRE WIDTH.

A

FL: the length of a structure that is elongated in one direction and relatively small in width.
FW: the width of the structure ^

29
Q

What is THRESHOLDING? IMAGE SEGMENTATION? BINARY IMAGE?

A

T: the simplest method of image segmentation. Creating binary images from a greyscale image.
IS: taking a smaller part of a whole image. Makes it easier to analyse. Like cropping an image for the part you want I think.
BI: image that only has 2 possible values for each pixel - most time it is B & W.

30
Q

What is TEXTURE SEGMENTATION?

A

To break large images up into Regions of Interest (ROI) and then to classify these regions. Done via thresholding.

31
Q

What is QUANTIFYING your data?

A

Removal of any subjectivity.

32
Q

What is STATISTICAL ANALYSIS?

A

The study of the collection, organisation, analysis, interpretation and presentation of data.