Digital_image_processing introduction ppt for basic understanding

Dr. Ajay Kumar Mallick,
NIT Hamirpur
Digital Image Processing (CS-323)
Lecture-1
Dr. Ajay Kumar Mallick
Department of Computer Science and Engineering
NIT Hamirpur, India

Outline
▪ Topics to Learn
1. Digital Image Representation
2. Defination of image
3. Difference among image processing, image understanding,
and computer vision
4. Paradigm for computerized processing
5. Examples of fields that use Digital Image Processing

Digital Image Representation
▪ Interest in digital image processing methods stems from two principal
application areas.
1. Improvement of pictorial information for human interpretation.
2. Processing of image data for tasks such as storage, transmission, and
extraction of pictorial information.

Defination of Image
▪ An image may be defined as a two-dimensional function, f(x,y), where x and
y are spatial (plane) coordinates, and the amplitude of f at any pair of
coordinates (x ,y) is called the intensity or Gray level of the image at that
point.
▪ When x, y, and the intensity values of f are all finite, discrete quantities, we
call the image a digital image.
▪ The field of digital image processing refers to processing digital images by
means of a digital computer.
▪ A digital image is composed of a finite number of elements, each of which
has a particular location and value. These elements of image are called
picture elements, image elements, pels, and pixels.

Difference among image processing, image understanding and computer vision
▪ Image processing is a discipline in which both the input and output of a
process are images.
▪ Computer vision refers to the discipline of Artificial Intelligence whose
ultimate goal is to use computers to emulate human vision, including learning
and being able to make inferences and take actions based on visual inputs.
▪ The area of image analysis (also called image understanding) is in between
image processing and computer vision.

Paradigm for computerized processing
▪ There are three paradigm for computerized processes, namely, :low-level,
mid-level, and high-level.
▪ Low-level processes that involve primitive operations such as image
preprocessing to reduce noise, contrast enhancement, and image sharpening.
▪ A low-level process is characterized by the fact that both input and output are
images.
▪ Mid-level processing on image involves tasks such as segmentation
descriptions of those objects to reduce them to form suitable for computer
processing, and classification (recognition) of individual objects.

Paradigm for computerized processing
.
▪ A mid-level process is characterized by the fact that inputs are generally
images, but its output are attributes extracted from those images (e.g. edges,
contours, and identity of individual objects).
▪ Finally, higher-level processes involves “making sense” of an ensemble of
recognized objects, as in image analysis, and performing the cognitive
functions normally associated with vision.
▪ Thus, we study here, image processing whose inputs and outputs are images,
and in addition, encompasses processes that extract attributes from images,
upto including recognition of individual objects.

Examples of fields that use Digital Image Processing
▪ We study this field in such a manner that leave no doubt regarding the breath
and importance of digital image processing.
▪ One of the simplest way to develop a basic understanding of the extent of
image processing applications is to characterize images according to their
sources (e.g. visual, X-ray, and so on).
▪ The principle energy source for images in use today is the electromagnetic
field energy spectrum.
▪ Other important sources include acoustic, ultrasonic and electronics (used in
microscope).

▪ Also, synthetic images, used for modelling and visualization are generated by
computers.
▪ In this context, Electromagnetic spectrum (EM) are the most familiar.
▪ EM waves can be conceptualized as propagating sinusoidal waves of varying
wavelength, each travelling with a wavelike pattern and moving at the speed
of light.
▪ Each mass-less particle contain a certain amount (or bundle) of energy.
▪ Each bundle of energy is called photon.

▪ If spectral bands are grouped according to the energy per photon, we have
range from gamma rays (highest energy) to radio waves (lowest energy) as
illustrated below.
▪ Fig1. EM Spectrum (Courtesy: Digital Image Processing, Gonzalez 3rd edition)

Examples of fields that use Digital Image Processing: Gamma –Ray Imaging
▪ The major application include nuclear medicine and astronomical
observations.
▪ In nuclear medicine, the approach is to inject a patient with radioactive
isotopes that emits gamma rays as it decays.
▪ Images are produces from the emission collected by gamma ray detectors.
▪ It is helpful in bone pathology, such as infections or tumours.

Examples of fields that use Digital Image Processing: Gamma –PET
▪ However, majority modality of nuclear imaging is called Positron Emission
Tomography (PET).
▪ The principle is same as X-ray, but the radioactive isotopes injected in the
patient emits positron as it decays.
▪ When a positron meets an electron, both are annihilated and two gamma rays
are given off.
▪ These are detected and 3D-rendering of the patient is created.

Examples of fields that use Digital Image Processing: Gamma –PET
(Courtesy: Digital
Image Processing,
Gonzalez 3rd
edition)

Examples of fields that use Digital Image Processing: X –Ray Imaging
▪ It is one of the oldest source of EM radiation used for imaging.
▪ In this, we have vacuum tube with cathode and anode.
▪ The cathode is heated, causing free electrons to release.
▪ These electrons flow at high speed to the positive charged anode.
▪ When the electron strike a nucleus, energy is released in the form of X-rays
radiations.

▪ The energy (or penetration power) of X-rays is controlled by a voltage applied
across the anode, and by the current applied to the filament in the cathode.
▪ The intensity of the X-ray is modified by absorption as they pass through the
patient, and the resulting energy falling on the filament develops it.
▪ Analogously, angiography is another major application in an area called
contract enhancement radiography.
▪ It helps to obtain images of blood vessels.

(Courtesy: Digital
Image Processing,
Gonzalez 3rd
edition)

Examples of fields that use Digital Image Processing:Ultravoilet band Imaging
▪ Application include- microscopy, biological images, and astronomical
observations.
▪ Ultraviolet light is used in fluorescence microscopy.
▪ Fluorescence is a phenomenon imply that when ultraviolet is directed upon it.
▪ The ultraviolet light itself is not visible, but when a photon of ultraviolet
radiation collides with an electron of fluorescent material atom, it elevates the
electron to a higher energy level.

Examples of fields that use Digital Image Processing:Ultraviolet band Imaging
▪ Subsequently, the excited electron relaxes to a lower level and emits light in
the form of lower-energy photon in the visible (red) light region.
▪ The resulting area (fluorescing area) shine against a dark background with
sufficient contrast to permit detection.
▪ Darker background, imply the efficiency of the instruments.

Examples of fields that use Digital Image Processing:Ultravoilet band Imaging
▪ Subsequently, the excited electron relaxes to a lower level and emits light in
the form of lower-energy photon in the visible (red) light region.
▪ The resulting area (fluorescing area) shine against a dark background with
sufficient contrast to permit detection.
▪ Darker background, imply the efficiency of the instruments.

Examples of fields that use Digital Image Processing:Ultraviolet band Imaging
(Courtesy: Digital
Image Processing,
Gonzalez 3rd
edition)

Examples of fields that use Digital Image Processing:Visible & Infrared band
▪ Imaging in this band out-weights by far all other in terms of breath of
application.
▪ The infrared band often is used in conjunction with visual imaging, so we
have grouped the visible and infrared bands for the purpose of illustration.
▪ A major area of visual processing is remote sensing which include several
bands in the visual and infrared regions of the spectrum.
▪ The table of thematic band of LANDSAT is to obtain and transmit image.
(Courtesy: Digital
Image Processing,
Gonzalez 3rd
edition)

▪
(Courtesy: Digital
Image Processing,
Gonzalez 3rd
edition)

▪ (Courtesy: Digital
Image Processing,
Gonzalez 3rd
edition)

Examples of fields that use Digital Image Processing: Microwave band
▪ The dominant application of imaging in microwaves based is radar.
▪ Th unique feature of imaging radar is its ability to collect data over virtually
any whether at any time , regardless of weather, or ambient lightening
conditions.
(Courtesy: Digital
Image Processing,
Gonzalez 3rd
edition)

Examples of fields that use Digital Image Processing: Radio band
▪ The radio waves are used in magnetic resonance imaging (MRI).
▪ This techniques places a patient in a powerful magnet and passes radio waves
through his or her body in short pulses.
▪ Each pulses causes a responding pulse of radio waves to be emitted by the
patient’s tissue.
▪ The location from where these signals originate and their strength are
determined by a computer, which produces a 2-D picture of the section of the
patient.
(Courtesy: Digital
Image Processing,
Gonzalez 3rd
edition)

Examples of fields that use Digital Image Processing: Radio band-MRI
(Courtesy: Chakraborty, Sabyasachi, Satyabrata Aich, and Hee-Cheol Kim. "3D textural,
morphological and statistical analysis of voxel of interests in 3T MRI scans for the detection of
Parkinson’s disease using artificial neural networks." Healthcare. 2020.

Examples of fields that use Digital Image Processing:Other form
▪
(Courtesy: Digital
Image Processing,
Gonzalez 3rd
edition)

Digital_image_processing introduction ppt for basic understanding

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