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Image Analysis > Lesson 2 > Flashcards

Lesson 2 Flashcards

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1
Q

What is a digital image composed of?

A

A large array of discrete dots called pixels.

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2
Q

What is the neighborhood of a pixel?

A

The pixels surrounding a given pixel.

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3
Q

What does greater spatial resolution mean?

A

More pixels are used to display images.

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4
Q

How can you halve the size of an image?

A

By taking out every other row and every other column.

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5
Q

What is the purpose of the preprocessing step in digital image processing?

A

To correct defects and enhance contrast for better feature analysis.

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6
Q

What are the three different color models mentioned?

A
  • RGB color model
  • CMYK color model
  • HSV color model
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7
Q

What is a point operation in image processing?

A

Applying a simple function y=f(x) to each gray value in the image.

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8
Q

What is the formula for calculating grayscale pixel value in scikit-image?

A

Y = 0.2125R + 0.7154G + 0.0721B.

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9
Q

What is the significance of the weights used in grayscale conversion?

A

They better represent human perception of red, green, and blue.

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10
Q

What are the effects of poor technical image quality?

A
  • Low contrast
  • Noise
  • Blurring
  • Aliasing
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11
Q

What does top-1 accuracy refer to?

A

Accuracy by comparing the top prediction with the correct class.

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12
Q

What types of noise can degrade an image signal?

A
  • Salt and pepper noise
  • Gaussian noise
  • Speckle noise
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13
Q

What is aliasing in images?

A

Occurs when a signal is sampled at slightly less than the period of the original signal.

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14
Q

What does image enhancement aim to achieve?

A

To make the result more suitable for a specific application.

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15
Q

What are the two main domains for image enhancement?

A
  • Spatial Domain
  • Frequency Domain
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16
Q

What is histogram equalization?

A

Mapping a roughly equal number of pixels to each intensity level for a flat histogram.

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17
Q

What is Otsu’s Method used for?

A

To determine the optimal threshold for separating background and foreground pixels.

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18
Q

What is adaptive thresholding?

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A

Calculating local thresholds with fixed block size surrounding each pixel.

19
Q

What type of intensity transformation can improve image appearance?

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A

Gamma transformations.

20
Q

What is the effect of contrast stretching?

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A

Improves the appearance of images for better segmentation and recognition.

21
Q

What is the function of a grayscale image to binary image conversion?

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A

A pixel becomes white if its gray level is greater than T, black if less than or equal to T.

22
Q

What is the purpose of smoothing in image processing?

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A

To reduce noise and improve image quality.

23
Q

What are the two types of blurs mentioned?

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A
  • Motion Blur
  • Out of focus Blur
24
Q

What is the formula for contrast stretching?

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A

Using percentiles to rescale intensity within a specified range.

25
What does a histogram indicate in a digital image?
The distribution of pixel intensities, showing darkness, brightness, and contrast.
26
What is the main goal of image segmentation?
To partition an image into meaningful segments for analysis.
27
What is the main output of the preprocessing step in image processing?
Images that are ready for further analysis.
28
What is the significance of image quality on deep neural networks?
Poor image quality can lead to misclassification by DNNs.
29
What can cause JPEG distortion in images?
Compression artifacts during image saving.
30
What is Adaptive Thresholding used for?
Better results when there is a large variation in background intensity ## Footnote Adaptive Thresholding helps in segmenting images by differentiating foreground from background based on varying light conditions.
31
What is the primary function of Point Operators?
They do not know anything about their neighbors ## Footnote Point Operators operate independently on each pixel without considering surrounding pixels.
32
What are the three steps involved in convolutions?
1. Position the mask over the current pixel 2. Form all products of filter elements with corresponding neighborhood elements 3. Add up all the products ## Footnote These steps are repeated for every pixel in the image.
33
What is the basic difference between convolution and correlation?
Convolution rotates the kernel by 180 degrees ## Footnote This distinction is important for understanding how the two processes affect image filtering.
34
What are the three types of kernel sizes used in smoothing operations?
* 3x3 Kernel * 5x5 Kernel * 7x7 Kernel ## Footnote Different kernel sizes affect the degree of smoothing applied to the image.
35
What is the purpose of the averaging mask?
Used for smoothing an image by averaging pixel values ## Footnote Averaging masks help reduce noise and detail in images.
36
How does the Gaussian smoothing filter work?
Based on the Gaussian probability distribution ## Footnote The standard deviation (σ) influences the shape of the Gaussian curve, affecting the smoothing effect.
37
What is the role of the median filter in image processing?
Removes noise while preserving edges ## Footnote Median filters replace each pixel value with the median value of neighboring pixels, effectively reducing noise.
38
What is meant by 'gradient' in image processing?
The direction of most rapid change in intensity ## Footnote The gradient helps identify edges and transitions in an image.
39
What is the edge strength defined by?
The gradient magnitude ## Footnote Edge strength indicates how strong an edge is based on changes in pixel intensity.
40
Fill in the blank: The Prewitt Operator is used for ______.
Edge detection ## Footnote Prewitt Operators calculate gradients to highlight edges in images.
41
What is the function of the Laplacian filter in image processing?
Used for image sharpening ## Footnote Laplacian filters enhance edges by emphasizing regions of rapid intensity change.
42
True or False: Spatial Filtering can only be used for smoothing images.
False ## Footnote Spatial Filtering can also be applied for sharpening and edge detection.
43
What does the term 'convolution' refer to in the context of image processing?
A mathematical operation that combines two functions ## Footnote In image processing, convolution typically involves applying a filter to an image.
44
What does the term 'smoothing' refer to in image processing?
The process of reducing noise and detail in an image ## Footnote Smoothing helps in creating a cleaner image for further analysis.

Image Analysis (2 decks)

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