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Questions and Answers
In digital image representation, what do the matrix elements of a digital image typically represent?
In digital image representation, what do the matrix elements of a digital image typically represent?
- The pixel/pel/picture element's gray levels. (correct)
- The color palette used in the image.
- The compression algorithm applied to the image.
- The metadata associated with the image file.
How is a digital image mathematically represented?
How is a digital image mathematically represented?
- As a single vector with pixel values.
- As a binary tree structure representing image features.
- As an MxN matrix where each element represents a pixel intensity. (correct)
- As a linked list of color codes.
What does the parameter 'L' represent in the mathematical representation of a digital image?
What does the parameter 'L' represent in the mathematical representation of a digital image?
- The average intensity value of all pixels.
- The total number of pixels in the image.
- The minimum intensity value in the image.
- The maximum intensity value in the image. (correct)
How does the representation differ between a monochrome and an RGB image regarding matrices?
How does the representation differ between a monochrome and an RGB image regarding matrices?
Why are matrix operations significant in digital image processing techniques?
Why are matrix operations significant in digital image processing techniques?
A pixel 'p' is located at coordinates (x, y). According to the definition of pixel neighbors, which of the following is NOT considered a direct neighbor of 'p'?
A pixel 'p' is located at coordinates (x, y). According to the definition of pixel neighbors, which of the following is NOT considered a direct neighbor of 'p'?
Given a pixel 'p', what does N(p) represent?
Given a pixel 'p', what does N(p) represent?
Which coordinates define the four diagonal neighbors of a pixel 'p' located at (x, y)?
Which coordinates define the four diagonal neighbors of a pixel 'p' located at (x, y)?
What does ND(p) represent in the context of pixel neighborhood?
What does ND(p) represent in the context of pixel neighborhood?
What is the relationship between N(p), ND(p), and N(p)?
What is the relationship between N(p), ND(p), and N(p)?
In the context of digital image representation, what constitutes a digital path between two pixels p and q?
In the context of digital image representation, what constitutes a digital path between two pixels p and q?
What is the significance of 'n' in defining a digital path from pixel p to pixel q, represented as (x, y), (x, y), ..., (xn, yn)?
What is the significance of 'n' in defining a digital path from pixel p to pixel q, represented as (x, y), (x, y), ..., (xn, yn)?
In the context of a digital path from pixel p to q, under what condition is the path considered a closed path?
In the context of a digital path from pixel p to q, under what condition is the path considered a closed path?
What determines whether a path is a 4-path, 8-path, or m-path?
What determines whether a path is a 4-path, 8-path, or m-path?
In image analysis, what condition must be met for two pixels, p and q, within a subset S to be considered connected?
In image analysis, what condition must be met for two pixels, p and q, within a subset S to be considered connected?
For a pixel p within a set S, what is defined as a 'connected component' in S?
For a pixel p within a set S, what is defined as a 'connected component' in S?
Under what condition is a set S called a 'connected set'?
Under what condition is a set S called a 'connected set'?
In image segmentation, if R represents a subset of pixels, under what condition is R considered a 'region' in an image?
In image segmentation, if R represents a subset of pixels, under what condition is R considered a 'region' in an image?
When are two regions (R_i) and (R_j) considered adjacent?
When are two regions (R_i) and (R_j) considered adjacent?
What characterizes regions that are considered 'disjoint'?
What characterizes regions that are considered 'disjoint'?
What defines the 'boundary' of a region R in a digital image?
What defines the 'boundary' of a region R in a digital image?
In the context of displaying color on a screen using bitmap data, how is RGB intensity determined for a 24-bit file?
In the context of displaying color on a screen using bitmap data, how is RGB intensity determined for a 24-bit file?
When displaying color using a 1, 4, or 8-bit file format, how is RGB intensity typically obtained?
When displaying color using a 1, 4, or 8-bit file format, how is RGB intensity typically obtained?
What is the primary purpose of halftoning in digital imaging?
What is the primary purpose of halftoning in digital imaging?
How do human eyes perceive a narrow area containing multiple pixels in the context of halftoning?
How do human eyes perceive a narrow area containing multiple pixels in the context of halftoning?
Which of the following devices commonly utilizes halftoning techniques?
Which of the following devices commonly utilizes halftoning techniques?
In digital halftoning, what determines the number of intensity levels that can be displayed?
In digital halftoning, what determines the number of intensity levels that can be displayed?
For an n x n pixel grid on a bilevel system, what is the maximum number of intensity levels that can be achieved using digital halftoning?
For an n x n pixel grid on a bilevel system, what is the maximum number of intensity levels that can be achieved using digital halftoning?
With reference to pixel grid patterns, what is the primary goal of initiating the pattern from the grid's center?
With reference to pixel grid patterns, what is the primary goal of initiating the pattern from the grid's center?
Besides minimizing the conturing effect, what other visual effect does a symmetric pixel grid pattern help minimize?
Besides minimizing the conturing effect, what other visual effect does a symmetric pixel grid pattern help minimize?
What is the main objective of dithering in image processing?
What is the main objective of dithering in image processing?
According to the material, what happens to perceived color appearance when using a low number of pixels in the context of dithering with two colors (Red & Blue)?
According to the material, what happens to perceived color appearance when using a low number of pixels in the context of dithering with two colors (Red & Blue)?
In the context of dithering techniques, which method involves selecting pixel colors that most closely match the average color in a given area?
In the context of dithering techniques, which method involves selecting pixel colors that most closely match the average color in a given area?
Which dithering technique involves the addition of random noise to pixels in order to smooth intensity borders?
Which dithering technique involves the addition of random noise to pixels in order to smooth intensity borders?
In error diffusion dithering, how is pixel intensity handled to achieve an appearance closer to the original image?
In error diffusion dithering, how is pixel intensity handled to achieve an appearance closer to the original image?
In the error diffusion dithering technique, if , , , and are the diffusion coefficients, what rule must they follow?
In the error diffusion dithering technique, if , , , and are the diffusion coefficients, what rule must they follow?
In typical error diffusion, if the coefficient to the right pixel is 7/16, to the pixel below is 5/16 and to the pixel to the left and below is 1/16, what is the coefficient to the pixel to the right and below?
In typical error diffusion, if the coefficient to the right pixel is 7/16, to the pixel below is 5/16 and to the pixel to the left and below is 1/16, what is the coefficient to the pixel to the right and below?
Which statement accurately summarizes the relationship between sampling and quantization in the context of digital image creation?
Which statement accurately summarizes the relationship between sampling and quantization in the context of digital image creation?
Consider a scenario where you have a grayscale image and you want to reduce the number of shades of gray it contains. Which image processing technique would be most applicable for this task?
Consider a scenario where you have a grayscale image and you want to reduce the number of shades of gray it contains. Which image processing technique would be most applicable for this task?
Imagine you have a high-resolution photograph that you want to display on a small, low-resolution screen without losing essential details. Which technique would be most effective in adapting the image for this display?
Imagine you have a high-resolution photograph that you want to display on a small, low-resolution screen without losing essential details. Which technique would be most effective in adapting the image for this display?
Flashcards
Digital Image Representation
Digital Image Representation
Representing a digital image with a matrix.
Digitalization
Digitalization
Process of converting an analog image to digital form.
Scan Line
Scan Line
A line used to convert a continuous image into a digital image.
Quantization
Quantization
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Sensor Array Projection
Sensor Array Projection
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Digital Image Matrix
Digital Image Matrix
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Coordinate System
Coordinate System
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Digital Image Definition
Digital Image Definition
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Image Matrix
Image Matrix
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4-Neighbors
4-Neighbors
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Diagonal Neighbors
Diagonal Neighbors
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8-Neighbors
8-Neighbors
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Digital Path
Digital Path
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Connected Component
Connected Component
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Region
Region
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Bitmap Image
Bitmap Image
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24-bit RGB
24-bit RGB
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Indexed Color
Indexed Color
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Halftoning
Halftoning
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Halftoned Grey Scale
Halftoned Grey Scale
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Dot Shapes
Dot Shapes
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pixel intensity grid
pixel intensity grid
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Dithering
Dithering
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random dithering
random dithering
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pixel intensity diffusion
pixel intensity diffusion
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Study Notes
- Intelligent Computing and Multimedia (ICM)
Digital Image Representation:
- Digital images undergo a process of digitalization.
- This involves concepts of sampling and quantization to generate an image.
- In the RGB image format, 256 gray levels are used to represent color intensity, with 256 levels (8 bits/pixel) generally considered sufficient to represent the gray levels.
- A digital image can be mathematically expressed as an MxN marix.
- M = rows with a range of 0 ≤ y ≤ M-1.
- N = column with a range of 0 ≤ x ≤ N-1.
- L = maximum intensity, with a range of 0 ≤ f(x,y) ≤ L – 1.
- Pixel coordinates are shown on coordinate system x,y
- The values of x, y, and f(x, y) are discrete and finite.
- The image's size is defined as max(x) x max(y); for example 1000 x 640.
- The gray level at a point (x, y) is defined as f(x, y) within the range of [0, 255].
- Gray level values can be normalized, thus laying in the range of [0, 1].
- A monochrome image is represented by a matrix, while an RGB image is represented by three matrices corresponding to different channels.
Relationship Between Pixels:
- A pixel p located at point (x, y) has neighboring pixels expressed as (x+1, y), (x-1, y), (x, y+1), (x, y-1).
- A set of these neighbor pixels are called 4-neighbors of p, is expressed as N₄(p).
- The four diagonal neighbors of p have coordinates: (x+1, y+1), (x+1, y-1), (x-1, y+1), (x-1, y-1), and are denoted by ND(p).
- ND(p) together with N₄(p) are called 8-neighbors of p, and is denoted by N₈(p).
- A digital path (or curve) from pixel p with coordinates (x, y) to pixel q with coordinates (s, t) is a sequence of distinct pixels with coordinates: (x₀, y₀), (x₁, y₁), ..., (xₙ, yₙ).
- In this sequence, (x₀, y₀) = (x, y), (xₙ, yₙ) = (s, t), and pixels (xᵢ, yᵢ) and (xᵢ₋₁, yᵢ₋₁) are adjacent for 1 ≤ i ≤ n, and n is the path's length.
- If (x₀, y₀) = (xₙ, yₙ), the path is considered a closed path.
- Paths can be defined as 4-, 8-, or m-paths, depending on the type of adjacency specified.
- A subset of pixels in an image is S.
- Two pixels, p and q, are connected in S if a path exists between them.
- For any pixel p in S, the set of pixels connected to it in S is known as a connected component in S.
- If S has only one conture, then the set S is considered a connected set.
- R is a region of the image if R is a connected set.
- Two regions, Ri and Rj, are adjacent if their union forms a connected set.
- Regions that are not adjacent are disjoint.
- The boundary (border, contour) of region R is a set of Region R that has one or more non-R neighbors.
Bitmap Images:
- For a 24-bit file, RGB intensity is directly obtained from the bitmap data.
- For 1, 4, or 8-bit files, RGB intensity is obtained from a Color Map.
Halftoning:
- A method for printing a range of colors with limited range in digital equipment.
- Narrow pixel areas cause human eye to perceive an average color.
- Examples: Monochrome printers
- Digital halftoning uses a pixel-grid pattern (rectangular).
- Intensity depends on the number of pixels that arrange each grid, and the intensity level supported by the equipment.
- intensity increase in bilevel systems with n x n pixels according to equation n²+1.
- The center of the grid should start to minimizing conturing effect and other visual effects (symmetric pattern).
Dithering:
- Dithering performs halftoning by minimizing resolution degradation.
- The appearance color will change if only using two colors (Red & Blue) and the number of pixels are low
- Dithering techniques include:
- Average dithering using pixel colors closest to the average color.
- Noise added to pixels to obtain intensity border smoothing (random dithering).
- Error diffusion between input and diffused pixel intensity.
- Pixel intensity diffuses to the right and bottom to obtain appearance close to the original image.
- Values to error diffusion must be a+ẞ+y+8 ≤ 1 with the known (α,β,γ,δ ) = (7/16, 3/16, 5/16, 1/16).
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