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Remote Sensing - RMS451 > Digital Image Analysis > Flashcards

Digital Image Analysis Flashcards

1
Q

What does digital image analysis accomplish?

A

Help detect, identify, measure and analyze…

features, objects, phenomena processed from digitally remotely sensed images

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2
Q

What are some examples of preprocessing?

A
  • detection & restoration of bad lines
  • geometric rectification or image registration
  • radiometric calibration and atmospheric correction
  • topographic correction
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3
Q

Image enhancement methods can be grouped into what three categories?

A

1 - contrast enhancement
2 - spatial enhancement
3 - spectral transformation

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4
Q

What are two important correction steps in image processing?

A

1 - Geometric corrections

2 - atmospheric corrections

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5
Q

Why may non-systematic error occur?

A
  • changes in RSS altitude
  • Increase in terrain elevation (image scale)

[about where things are vertically]

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6
Q

What does geometric correction involve?

A

1) digital rectification - the geometry of an
image is made planimetric (i.e., no relief )
2) resampling - extrapolating data values into a new grid

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7
Q

During geometric rectification, what happens with image coordinates?

A

The image coordinates of Ground Control Points (GCPs) are matched to their true positions in ground coordinates (measured from a map or previously rectified image)

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8
Q

True or false: Resampling does not alter original data

A

True

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9
Q

What is a downside of the Nearest Neighbour method of resampling?

A

It may result in some pixel values being duplicated or lost

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10
Q

What does the Bilinear interpolation resampling method involve?

A

Estimates output cell value by taking the weighted average of four pixels in the original image nearest to the new cell location

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11
Q

From least smooth to most smooth, list the three methods of resampling.

A

1) Nearest neighbour
2) Bilinear interpolation
3) Cubic convolution

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12
Q

The Cubic convolution resampling method estimates the cell output value by calculating the average of the ______ __ input cells to the new cell location.

A

Closest 16 input cells

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13
Q

“Radiometric noise” is the collective term for what four types of variances?

A

1) scene illumination
2) atmospheric conditions
3) sensor noise
4) Response characteristics

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14
Q

What do radiometric corrections aim to do?

A
  • reduce influence of “noise”
  • facilitate image analysis and interpretation
  • enhance quantitative measurements
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15
Q

True or false: Radiometric correction is required for electro-optical sensors

A

True

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16
Q

Image BVs must be normalized across and between what?

A
  • image scenes
  • spectral bands
  • image acquisition dates
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17
Q

How is sun elevation correction done?

A

dividing each pixel value in an image by the sine of the solar elevation angle for the time and location of image acquisition

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18
Q

What is needed to account for the seasonal change of earth-sun distance?

A

Sun elevation correction

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19
Q

Does adsorption and scattering does what to the EM energy illuminating the ground surface?

A

Reduces the EM energy illuminating the ground surface

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20
Q

What does issue atmospheric scattering introduce?

A

“haze”; reducing contrast

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21
Q

The following is one method of accomplishing what?

“examine BVs in an area of shadow OR very dark object (e.g., large, clear lake) · reflectance from such object in the near-IR region = 0 - if BVs > 0, then assumed to be due to atmospheric scattering - The “offset” value is subtracted from all pixels in that band”

A

Haze compensation

22
Q

Relative radiometric correction is applied to do what, and how can it be done?

A
  • Normalize the intensities amoung the different bands within an image

Can be done by:
> single-image adjustment using histogram adjustment
- multiple-data image normalization using regression

23
Q

Three methods for contrast enhancement are…?

A

1 - linear contrast stretch
2 - histogram equilization
3 - special stretch

24
Q

What is an image histogram?

A

A graphical representation of the BVs that comprise an image, with BVs (x-axis) and their frequency of occurrence (y-axis)

25
Q

What does the linear contrast stretch image enhancement technique do, and when does it not work well?

A
  • Makes light-toned areas appear lighter & dark toned areas appear darker.
  • Does not work well if one wants to see more detail in lighter or darker toned areas

[Strange way of remembering: “Linear” sounds like “liar”. People lie so that the rich get richer and the poor get poorer. This is not good for seeing the very rich or very poor as individual humans, but rather encourages social classism.]

26
Q

What does the histogram equalization stretch image enhancement technique do?

A
  • Assigns more display values to higher frequency of BVs and less display values to lower frequency of BVs
  • (enhances higher frequency BVs, reduces contrast in very light and very dark parts)

[Funny way of remembering: in HISTOry we tend to remember the more frequent fashions]

27
Q

What is the special stretch image enhancement technique?

A

Assigning the entire display range to a particular range of image values (to get brighter and greater contrast)

28
Q

What does Contrast enhancement focus on?

A

Optimal use of colours available on display to match with image BVs collected by a sensor

29
Q

What does spatial enhancement techniques do?

A
  • Emphasize the spatial relationship of image pixels
  • define homogeneous regions & detect & sharpen boundary discontinuities between adjacent pixels with significant variation in BVs
30
Q

Image areas of high spatial frequency show changes in BV as what?

A

Abrupt changes in BV over a small number of pixels (rough texture)

eg. geologic faults, lake edges, roads, airports

31
Q

What do areas of low spatial frequency look like?

A

“Smooth” with little variation in BV over a relatively large number of pixels

eg. water bodies, agricultural fields

32
Q

What do spatial filters method of spatial enhancement do?

A

Uses user-defined filters to emphasize or suppress image data of different spatial frequencies

33
Q

Are low-pass filters or high-pass filters used to smooth/blur the appearance of an image?

A

Low-pass filter

34
Q

What does spatial filtering involve?

A

“involves passing a window of know pixels of dimension (e.g., 3X3, 5X5, 7X7, etc.), applying a mathematical operation to the pixel values within that moving window , and creating a new image where the value of the central pixel is the result of the mathematical operation”

35
Q

If a high-pass filter is added to an original image, what kind of enhancement will be achieved?

A
  • high frequency enhancement

- edge-enhanced image

36
Q

What are directional filters?

A

Digital filters that enhance features in particular directions

37
Q

What is spectral transformation?

A

manipulation of multiple bands of data to generate more useful information

38
Q

What 3 methods are involved in spectral transformations?

A

1 - band rationing
2 - vegetation indices
3 - principal component analysis

[Memory aid in progress]

39
Q

What is band ratioing?

A
  • Dividing BVs of one band by BVs of another band
  • Stretches the resulting image for better visualization
  • brighter tones indicate larger differences in the spectral response
  • variations in scene illumination are minimized
40
Q

What must be removed before band ratioing takes place?

A

Image noise and atmospheric haze

41
Q

What are vegetation indices (VI) used for?

A

Discriminating between stressed and non-stressed vegetation

42
Q

What does healthy green vegetation respond in the NIR portion and visible red portions?

A

1) reflects strongly in NIR portion

2) absorbs strongly in visible red portion

43
Q

What does NDVI stand for, and what is it used for?

A
  • “Normalized Difference Vegetation Index”

- assess green biomass and as a proxy to overall ecosystem health

44
Q

What does PCA stand for?

A
  • “Principal Component Analysis”
45
Q

What is Principal Component Analysis used for?

A
  • PCA is statistical technique used to reduce data redundancy
  • “mathematical transformation – plot pixel values from 2 bands on a scatter diagram”
46
Q

What happens with primary colours in a colour composite image?

A

Each primary colour is assigned to a separate spectral band

47
Q

What are the two approaches to image classification?

A
  • Supervised classification

- Unsupervised classification

48
Q

What is involved in supervised calculation?

A

Analyst identifies in the image, homogeneous representative samples of different cover types (information classes) of interest to be used as training areas

49
Q

What is involved in unsupervised classification?

A

Spectral classes are first grouped based solely on DNs of the band selected for use

  • various statistical methods used to cluster all pixels in an image into spectral groups
  • analyst specified the number of groups
50
Q

What are the most frequently used classifiers of supervised classification?

A
  • minimum distance classifier
  • parallelepiped classifier
  • maximum likelihood classifier

Remote Sensing - RMS451 (3 decks)

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