Image Processing and Human Vision Quiz

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Questions and Answers

What is the approximate range of the focal length of the lens in humans?

10 mm to 13 mm

14 mm to 17 mm (correct)

18 mm to 20 mm

12 mm to 15 mm

What phenomenon causes the perceived brightness to appear scalloped at boundaries of different intensities?

Intensity modulation

Mach bands (correct)

Simultaneous contrast

Brightness adaptation

In the phenomenon of simultaneous contrast, how does the perceived brightness of a center square change?

It becomes darker as the background gets lighter. (correct)

It remains unchanged regardless of the background.

It becomes the same color as the background.

It becomes brighter as the background gets darker.

Which constant is utilized in the energy formula for light, denoted as E = h?

Planck's constant Signup and view all the answers

What determines the colors perceived in an object by humans?

The nature of the light reflected from the object Signup and view all the answers

What is the formula to calculate the number of bits required to store a digitized image?

b = M × N × k Signup and view all the answers

Which of the following correctly defines intensity resolution?

It indicates the smallest measurable change in intensity level. Signup and view all the answers

How is a 'k-bit image' defined?

An image with L = 2^k gray levels. Signup and view all the answers

What does spatial resolution measure in digital images?

The number of pixels per unit area or distance. Signup and view all the answers

What is the primary purpose of interpolation in image processing?

To estimate unknown pixel values using known data. Signup and view all the answers

What unit is used to measure illumination?

Lumen per square meter (lm/m2) Signup and view all the answers

How much illumination does the sun produce on a clear day?

Up to 90,000 lm/m2 Signup and view all the answers

What is the gray level of an image typically represented as?

An interval from Lmin to Lmax Signup and view all the answers

What is the reflectance value for snow?

0.93 Signup and view all the answers

What is the typical illumination level found in a commercial office?

1000 lm/m2 Signup and view all the answers

What is the reflectance value for black velvet?

0.01 Signup and view all the answers

What does the digitizing process involve in image sampling?

Digitizing coordinate values and amplitude values Signup and view all the answers

In the context of image representation, what does 'M × N' represent?

The dimensions of the image array Signup and view all the answers

What is the primary function of the cornea in the human eye?

To cover the anterior surface of the eye Signup and view all the answers

How do cones differ from rods in terms of vision?

Cones are primarily responsible for color vision Signup and view all the answers

What role does the choroid play in the structure of the human eye?

It provides a major source of nutrition to the eye Signup and view all the answers

What occurs at the blind spot in the human eye?

There are no visual receptors present Signup and view all the answers

What is the primary characteristic of rod vision?

It is sensitive to low levels of illumination Signup and view all the answers

Which of the following best distinguishes the lens of the eye from ordinary optical lenses?

The lens of the eye is flexible Signup and view all the answers

Why can humans resolve fine details with their cone vision?

Each cone is connected to its own nerve ending Signup and view all the answers

What happens when light from an object is properly focused in the eye?

It is imaged on the retina Signup and view all the answers

What is the complement of the set A in a gray-scale image defined as Ac?

{(x, y, K - z) | (x, y, z) ∈ A} Signup and view all the answers

Which operation is used to find the union of two gray-scale images A and B?

{max(a, b) | a ∈ A, b ∈ B} Signup and view all the answers

In single-pixel operations, how is the new intensity value determined?

Based solely on the intensity at the pixel itself Signup and view all the answers

What is the purpose of intensity interpolation in geometric transformations?

To assign intensity values to newly created pixels after transformation Signup and view all the answers

Which of these best describes neighborhood operations in image processing?

They use values from a specified set of neighboring pixels to determine a pixel's value. Signup and view all the answers

Which transformation is referred to as rubber-sheet transformation?

A spatial transformation combined with intensity interpolation Signup and view all the answers

What is the primary element represented by z in the triplet (x, y, z) of a gray-scale image?

Intensity level of the pixel Signup and view all the answers

How is the maximum value in the union of two sets A and B determined?

By selecting the higher pixel value from each image Signup and view all the answers

What is the main purpose of using interpolation in digital cameras?

To produce a larger image or create digital zoom Signup and view all the answers

Which interpolation method uses only the nearest neighbor to determine the intensity of a pixel?

Nearest Neighbor Interpolation Signup and view all the answers

In bilinear interpolation, how many nearest neighbors are used to determine the intensity value of a point?

Four Signup and view all the answers

What is the equation used to calculate the Euclidean distance between two pixels p and q?

De(p, q) = [(x-s)² + (y-t)²]¹/² Signup and view all the answers

In bicubic interpolation, how many coefficients are determined based on the nearest neighbors?

16 Signup and view all the answers

What property describes that the distance between two pixels is always non-negative?

Non-negativity Signup and view all the answers

Which distance measure is characterized by the formula D4(p, q) = |x-s| + |y-t|?

City Block Distance Signup and view all the answers

What is the main feature of the distance measure D(p, q) = D(q, p)?

Symmetry Signup and view all the answers

Study Notes

Course Information

Course Title: Introduction to Computer Vision
Course Code: CPS834/CPS8307
Instructor: Dr. Omar Falou
University: Toronto Metropolitan University
Semester: Fall 2024

Digital Image

Digital Image: A two-dimensional function where x and y are spatial coordinates. The amplitude of f at the point (x,y) is called intensity or gray level (f(x,y)).
Pixel: The fundamental elements of a digital image.

Image Sources

Electromagnetic (EM) energy spectrum (Gamma rays, X-rays, ultraviolet, visible, infrared, microwaves, radio waves).
Acoustic
Ultrasonic
Electronic
Synthetic images produced by a computer

Electromagnetic (EM) Spectrum Examples

Gamma-ray imaging: Used for nuclear medicine, astronomical observations, microscopy, & biological imaging.
X-rays: Used for medical diagnostics, industrial applications, & astronomy.
Ultraviolet: Used for lithography, industrial and astronomical observations.
Visible & infrared bands: Used for light microscopy, astronomy, remote sensing, industry, and law enforcement.
Microwave band: Used for radar.
Radio band: Used for medicine (MRI) and astronomy.

Examples of Imaging Techniques

Gamma-ray imaging (Bone scan, PET image, Cygnus Loop, Gamma radiation)
X-ray imaging (Chest X-ray, Aortic angiogram, Head CT, Circuit boards)
Ultraviolet imaging(Normal corn, Smut corn, Cygnus Loop).
Light microscopy imaging (Taxol, Cholesterol, Microprocessor, Nickel oxide, Surface of audio CD, Organic superconductor).
Visual and Infrared imaging (LANDSAT satellite images of the Washington, D.C. area).

Automated Visual Inspection

Examples of manufactured goods that are often checked using image processing (A circuit board controller, Packaged pills, Bottles, Air bubbles in plastic products, Cereal, Image of intraocular implant).

Automated Visual Inspection - Results

Results of automated reading of the plate content by the system.
The area in which the imaging system detected the plate.

Example of Radar Image

Spaceborne radar image of mountains in Southeast Tibet.

Example of MRI

MRI images of a human knee and spine.

Example of Ultrasound Imaging

Examples of ultrasound imaging(Baby, Another view of baby, Thyroids, Muscle layers showing lesion).

Image Processing → Computer Vision

High-level: Object detection, recognition, shape analysis, tracking, and use of artificial intelligence and machine learning.
Image Analysis: Segmentation, image registration, and matching.
Low-level: Image enhancement, noise removal, restoration, feature detection, and compression.

Image Processing Problems

Image acquisition, Image enhancement, Image restoration, Morphological processing, Segmentation, Representation & description, Object recognition, Image compression.

Element of Visual Perception

Although the digital image processing field is based on mathematical and probabilistic formulations, human intuition and analysis also play a central role. The choice of technique often depends on subjective visual judgments.
Developing a basic understanding of human visual perception is essential.

Structure of the Human Eye

Cornea: Tough, transparent tissue covering the anterior surface of the eye.
Sclera: Opaque membrane enclosing the remainder of the optic globe.
Choroid: Lies beneath the sclera, containing a network of blood vessels, the major source of nutrition to the eye.
Lens: Absorbs infrared and ultraviolet, but excessive amounts can damage the eye.
Retina: The inner membrane lining the posterior portion of the eye's wall, where light from an object outside the eye is imaged.

Receptors

Receptors (neurons): distributed over the surface of the retina.
Divided into cones and rods.
Cones (neurons 6-7 million): Primarily located in the fovea (central portion), highly sensitive to color and details.
Rods (75-150 million): Distributed over the retina, highly sensitive to dim light.

Blind Spot

Figure 2.2 shows the density of rods and cones in a cross-section of the right eye, passing through the optic nerve's emergence point.
Blind spot: absence of receptors, radially symmetrical around the fovea.

Image Formation in the Eye

The eye's lens is flexible, unlike ordinary optical lenses; its focal length varies.

Brightness Adaptation and Discrimination

Perceived brightness is not solely determined by intensity.
Visual system tends to undershoot or overshoot around the boundary of regions with different intensities (Mach bands).
Simultaneous contrast: a region's perceived brightness depends on the surrounding regions.

Optical Illusions

Examples of well-known optical illusions.

Light and EM Spectrum

Colors humans perceive are determined by the reflected light wavelengths from an object.
Wavelengths for example: green roughly 500 to 570 nm.

Light and EM Spectrum – continued

Monochromatic light: devoid of color. Intensity varies from black to white, resulting in grayscale images.
Chromatic light bands: the range of wavelengths that create color.
Radiance (W, watts): the total energy emitted by a light source.
Luminance (Im, lumens): the amount of perceived light by an observer.
Brightness: a subjective descriptor of light perception.

Image Acquisition

Transforming light energy into digital images.
Components: energy, filters, power source, housing, sensing material, output voltage waveform.
Images can be acquired using single sensors or sensor strips (linear or circular).

Simple Image Formation Model

Model of image formation: f(x,y) = i(x,y) * r(x,y).
i(x,y): Illumination intensity at a point (x,y).
r(x,y): Reflectance or transmissivity at (x,y) describing the object's light interaction.

Components of Image Formation Models

f(x,y) : Intensity image at coordinates (x,y)
i(x,y) : Illumination component at (x,y).
r(x,y) : Reflectance component at (x,y), representing the object's light reflection.

Some Typical Illumination Ranges

Lumen: a unit of light flow or luminous flux
Lumen per square meter (lm/m²): The metric unit used to quantify illuminance of a surface.
Typical illumination levels: daytime (clear & cloudy), evening (moonlight), commercial office.

Some Typical Reflectance Ranges

Different materials have different reflectance levels.

Gray Level

Intensity of a monochrome image.
Common gray scale is [Lmin, Lmax] (0-black, 255-white).

Image Sampling and Quantization

Digitizing image coordinates and amplitude values: converting continuous into discrete values.
Sampling: the division of the image into discrete samples across the x and y axis. Pixels.
Quantization: dividing the range of light intensities values to assigned to each coordinate into discrete values. These discrete values are often represented by the number of bits assigned to the pixel..

Coordinate Convention

Defining the origin (0,0) and orientation (x-axis, y-axis) of the coordinate system, typically positioned at top-left corner within a frame.

Representing Digital Images

Representing images as a matrix where the integer values within the matrix correspond to pixel values (intensity).

Representing Digital Images – Continued

Discrete intensity interval: [0, L-1] with L = 2k (where k is the bit depth).
Stored number of bits, b, for an image of size M×N.
Image with 256 possible gray levels, often referred to as 8-bit image.

Representing Digital Images – Table

Table showing number of bits necessary for different image sizes and bit depths.

Coloured Image

Represented by RGB channels.
RGB: Red, Green, Blue

Spatial and Intensity Resolution

Spatial resolution: smallest discerned detail in an image (e.g.; dots per inch).
Intensity resolution: the smallest discernible change in an image intensity (e.g., bits).

Image Interpolation

Process of estimating unknown image values using known values.
Methods- Nearest Neighbor, Bilinear, Bicubic.

Distance Measures

Pixel distance metrics, such as Euclidean, City Block, and Chessboard distances, define ways to measure the proximity between pixels in a digital image.

Mathematical Operations in Digital Image Processing

Array operations are distinct from matrix operations.
Matrix product is a mathematical operation involving matrices.
Array product involves the element-wise multiplication of corresponding elements in image arrays.

Linear vs. Nonlinear Operations

Additivity: H(a1f1(x,y)+a2f2(x,y)) = a1H(f1(x,y)) + a2H(f2(x,y)).
Homogeneity: H(af(x,y)) = aH(f(x,y))

Arithmetic Operations

Basic operations are used for manipulating pixel values, using addition, subtraction, multiplication, and division.

Example: Addition of Noisy Images for Noise Reduction

Method of reducing noise in images, such as those from astronomical observations, by averaging multiple noisy images.

Example: Image Subtraction: Mask Mode Radiography

Method of enhancing contrast in images, such as X-ray images, by subtracting a mask image from a live image.

Example: Image Multiplication

Images are multiplied together to change or enhance characteristics within the images, such as modifying highlighting or shading within an image.

Set and Logical Operations

Set theory operations are used for pixel-based image manipulation.
Set operations allow using logical operations to create new images by comparing pixel values from different image sets.

Set and Logical Operations – Continued

The image values can be represented using set theory and the resulting sets can be used to perform a variety of image operations on a pixel-basis.

Spatial Operations

Single-pixel operations and neighborhood operations. These affect pixel values based on either the intensity of a single pixel value, or pixel values from neighboring pixels.

Geometric Spatial Transformations

Transforming coordinate systems from one image to another, such as enlarging, shrinking, or rotating images.

Geometric Spatial Transformations – Continued

Affine transform: A commonly used spatial transformation that encompasses scaling, rotation, and translation of images.

Intensity Assignment (Forward and Inverse Mapping)

Methods of assigning pixel values in output images based on their corresponding coordinates in input images to maintain spatial integrity during transformations such as rotation.

Example: Image Rotation and Intensity Interpolation

Different methods of assigning intensities to new locations in rotated images based upon nearest neighbor, bilinear, and bicubic interpolation.

Image Registration

Methods for aligning images; determining how one image is positioned related to another; usually based on known correspondences between landmarks between images.

Image Registration – continued

Tie points or control points are used to align (register) images. A bilinear approximation model: mathematical equation to map images (by finding a transformation function that models the relationship between images).

Image Transform

Transforming input and output images for different image process applications. Forward and inverse transformation kernel functions can be used to transform between domains. The transform domain is often different than the spatial domain and may facilitate operations that are difficult or impossible to complete on direct image transformations.

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Description

Test your knowledge on image processing concepts and human visual perception. This quiz covers topics such as focal length, brightness perception, color detection, and image resolution. Perfect for students of optics and digital imaging.