Image Representation in Computer Science

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A digital image can be considered as a discrete representation of data possessing both spatial and intensity

colour

The two-dimensional (2-D) discrete, digital image I (m,n) represents the response of some sensor at a series of fixed positions in 2-D Cartesian

coordinates

The individual picture elements or pixels of the image are referred to by their 2-D (m, n)

index

The conversion from a set of numbers to an actual image is achieved through a ______ map.

colour

The most common colour map is the ______, which assigns all shades of grey from black to white according to the signal level.

greyscale

In certain instances, it can be better to display intensity images using a ______ map.

false-colour

False colour can also serve to delineate certain features or structures, making them easier to identify for the human ______.

observer

The resolution of an image source can be specified in terms of three quantities: Spatial resolution, Temporal resolution, and ______ resolution.

quantization

Match the following image attributes with their definitions:

Spatial resolution = The dimensions of the image in terms of pixels Temporal resolution = Number of images captured in a given time period False-colour map = Assigns colours to numerical values in an image Greyscale = Assigns shades of grey from black to white according to the signal level

Match the following image types with their descriptions:

Intensity image = Contains a single numerical value at each pixel location True colour image = Represents the full spectrum of colours as a triplet vector at each pixel location Digital image = Discrete representation of data possessing both spatial and intensity Astronomical image = Often displayed using false-colour maps to highlight structure and finer detail

Match the following terms related to image display with their meanings:

Greyscale (left) = Displays an astronomical intensity image using shades of grey from black to white False colour (right) = Displays an astronomical intensity image using non-grey colours to highlight certain features or structures Jet colour map = Used to highlight the structure and finer detail of an astronomical intensity image using a linear colour scale Colour map = Assigns specific shades of colour to each numerical level in an image

Match the following attributes of an image source with their explanations:

Column by row dimensions = Defines the number of pixels used to cover the visual space captured by the image Continuous capture system = Captures a specified number of images in a given time period Video frame = An individual image captured in a video sequence Resolution = Defines the representational power of an image

Match the following statements about false-colour images with their reasons for usage:

Enhances human sensitivity to colour = Uses non-grey colours to represent intensity, as human visual system is more sensitive to colour than shades of grey Highlights specific features or structures = Makes it easier for human observers to identify certain elements in images Commonly used in medical and astronomical images = Due to its ability to highlight details and structures that may not be easily discernible in greyscale

Match the following image processing terms with their definitions:

Spatial resolution = The level of detail in an image, determined by the number of pixels Temporal resolution = The number of frames per second in a video Discretization = The process of converting a continuous signal into a discrete signal Intensity map = A representation of pixel intensity values in an image

Match the following terms related to image representation with their descriptions:

Digital image = A discrete representation of data with spatial and intensity information Pixel = The smallest element of an image, defined by its 2-D index Image origin = The reference point for the positioning of pixels in an image Cartesian coordinates = A system for locating points in a plane using distances from two perpendicular lines

Match the following concepts in MATLAB® with their meanings:

I(m,n) = The response of a pixel located at the mth row and nth column in an image, according to MATLAB® convention Column–row convention = An alternative method for designating rows and columns in an imaging system Top-left image origin = The starting point for the positioning of pixels in an image, as per MATLAB® convention Sampling process = The procedure for converting a continuous spatial signal into a discrete digital image

Match the following image types with their characteristics:

False colour = Assigning artificial colors to represent grayscale levels for easier feature identification Standard image types = Common categories of images, such as binary, grayscale, and color images Multidimensional signal = Treating an image as a complex signal with spatial and intensity dimensions Colour map = A scheme for assigning colors to represent intensity levels in an image

Match the following terms related to Omar Al-Mukhtar University's Computer Science Department with their descriptions:

Image Processing #1 = A specific course covering the fundamental concepts of representing and processing digital images Dr Tahani Almabruk = The instructor responsible for teaching Image representation and related topics Al-Beyda/ Libya = The location of Omar Al-Mukhtar University's Computer Science Department 2-D Cartesian coordinates = A system for graphing points on a two-dimensional plane using x and y axes

Test your knowledge about the representation of images in computer science, including basic notation, image types, and formats. Explore the concept of digital images as a discrete representation of data with spatial and intensity information.

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