Digital Image Processing - Ch1: Introduction

Digital Image Processing - Ch1: Introduction

• Digital Image Processing is a field of processing digital images.
• The study of digital images involves two-dimensional functions (f(x, y)), where x and y represent spatial coordinates.
• The amplitude of the function (f) is referred to as the intensity or gray level at a particular point (x, y).
• Digital images are composed of pixels (picture elements).
• Digital image processing aims to improve pictorial information for human interpretation, enhance images, and process image data for storage, transmission, and representation in autonomous machine perception.
• A digital image processing system consists of:
  • Image acquisition
  • Image enhancement
  • Image restoration
  • Colour image processing
  • Image compression
  • Morphological processing
  • Segmentation
  • Object recognition
  • Representation and description

Course Description

• Topics in the course will include: Introduction, Digital image fundamentals, Intensity Transformations and Spatial Filtering, Filtering in the Frequency Domain, and Image Restoration.

Course Textbook

• Digital Image Processing by Rafael C. Gonzalez & Richard E. Woods, Addison-Wesley, 2008.

Chapter Outline (Introduction)

• What is Digital Image Processing?
• The Origins of Digital Image Processing.
• Examples of Fields that Use Digital Image Processing.
• Fundamental Steps in Digital Image Processing
• Components of an Image Processing System

What is Digital Image Processing?

• Digital image processing involves processing digital images where the x and y coordinates define finite elements (pixels).

Image Processing & Image Analysis & Computer Vision

• Computer vision is a field of AI that allows systems to derive meaningful information from visual inputs (images, videos, etc.).
• It emulates human vision and allows for making inferences and taking actions.
• Digital image analysis focuses on describing and recognizing image contents.
• Feature extraction involves acquiring higher-level image information (e.g., shape, color).
• Pattern classification identifies objects in images based on extracted features.

Image Processing & Image Analysis & Computer Vision - Digital Image Processing Focuses

• Improvement of pictorial information for human interpretation (e.g., compression, enhancement).
• Processing of image data for storage, transmission, and representation for autonomous machine perception.
• Image processing involves algorithms that modify input images to create new images.

What is Digital Image Processing? (Levels)

• Three levels of digital image processing are recognized, from image processing to computer vision.
• Low Level Processes (Image Processing):
• Mid Level Processes (Image Analysis):
• High Level Processes (Computer Vision):

Image Processing Applications

• Medical Field: Image Enhancement
• Handwriting recognition
• Face detection
• Iris recognition
• Noise Removal

The Origins of Digital Image Processing

• Early examples of digital image production existed even before digital computers.
• Early methods often resulted in poor image quality due to limitations in reproduction mechanisms.
• Digital image processing began to develop in conjunction with the development of digital computers.
• The first images of the moon processed by computer were significant advancements.
• Medical imaging (CT, X-rays) emerged in the 1960s.
• Digital images became commonplace in other fields, like geography, archaeology, and physics.

Examples of Fields that Use Digital Image Processing - Electromagnetic Spectrum

• Electromagnetic (EM) waves, consisting of both waves and particles, are used for image analysis from various bands of the EM spectrum (e.g. Gamma waves, X-rays, Ultraviolet, Visible, Infrared, Micro, Radio waves).
• Specific parts of the spectrum are chosen for image analysis based on their suitability to highlight properties of the object through reflection or penetration.

Gamma-Ray Imaging

• Major use in nuclear medicine (radioactive material injection).
• Used to detect tumors in the brain and lungs, as well as for astronomy.

X-Ray Imaging

• Mainly used in medical imaging but also in astronomy.
• Emission is produced by heating a cathode.
• Digital X-ray can be created by digitizing analog images or by electronic image capture.
• X-ray imaging aids in CT scans.

Ultraviolet Band

• Commonly used in microscopy, lasers, biological imaging, and astronomical observation.

Imaging in the Visible and Infrared Bands

• Visible light and infrared imaging are frequently used in conjunction.
• Applications include satellite imagery (observation and prediction).
• Examples of these types of imaging include analyzing hurricane structures

Remote Sensing

• An application of visible and infrared bands for satellite imaging.
• Different band analysis provides different perspectives on subjects (e.g., changes in a river over time)

Imaging in the Visible Bands

• Applications include automated visual inspection of manufactured goods.

Imaging in the Microwave Band

• Radar is the most prominent application using microwave waves for imaging.
• It can penetrate clouds and vegetation which makes it possible to collect information any time.
• Flash cameras produce microwave pulses which reflect to produce a snapshot of the object to be detected

Imaging in the Radio Band

• Used largely in medical applications and astronomy.
• Magnetic Resonance Imaging (MRI) is a significant medical application.
• The method involves measuring the strength and location of pulses emitted by the body when placed in a strong magnetic field.

Other Imaging Modalities

• Many different types of images can be collected for the same object. The object itself and how it interacts with the wave that produces the image as well as the receiver (human eye or instrument) determine what is observed.
• Some examples include acoustic and electron microscopy.

Acoustic Imaging

Details on acoustic imaging, including the use of ultrasound to create two-dimensional images of unborn babies, are given.

Electron Microscopy

• Electron Microscopy is a modality used for imaging

Fractals (Synthesis Images)

• Fractals are computer-generated images based on mathematical models that create beautiful shapes and patterns.

Fundamental Steps in Digital Image Processing

• The key processes within digital image processing are presented as a flowchart/diagram. These include: Image Acquisition, Image Enhancement, Image Restoration, Color Image Processing, Image Compression, Morphological Processing, Segmentation, and Object Recognition, with the different processes represented as blocks, with arrows connecting them

Components of an Image Processing System

• Describes the components comprising a digital image processing system, from the computer to software components, storage, and communication.
• The system components include various types of hardware, software components and networking components.

This quiz explores the basics of Digital Image Processing, focusing on its fundamental concepts, functions, and components. Topics include image acquisition, enhancement, restoration, and techniques such as segmentation and object recognition. Test your understanding of this essential field in processing digital images.