image processing image enhancement and filtering

Digital Image
Processing
2nd Edition
S. Sridhar
© Oxford University Press 2016. All rights reserved.

Chapter 1
Introduction to Image Processing

Nature of Image Processing
• Images are everywhere! Sources of Images are paintings,
photographs in magazines, Journals, Image galleries, digital
Libraries, newspapers, advertisement boards, television and
Internet.
• Images are imitations of Images.
• In image processing, the term ‘image’ is used to denote the
image data that is sampled, quantized, and readily available in
a form suitable for further processing by digital computers.

IMAGE PROCESSING ENVIRONMENT

Reflective mode Imaging
• Reflective mode imaging represents the
simplest form of imaging and uses a sensor to
acquire the digital image. All video cameras,
digital cameras, and scanners use some types
of sensors for capturing the image.

Emissive type imaging
• Emissive type imaging is the second type, where the
images are acquired from self-luminous objects
without the help of a radiation source. In emissive
type imaging, the objects are self-luminous. The
radiation emitted by the object is directly captured
by the sensor to form an image. Thermal imaging is
an example of emissive type imaging.

Transmissive imaging
• Transmissive imaging is the third type, where
the radiation source illuminates the object.
The absorption of radiation by the objects
depends upon the nature of the material.
Some of the radiation passes through the
objects. The attenuated radiation is sensed
into an image.

Image Processing
• Optical image processing is an area that deals with
the object, optics, and how processes are applied to
an image that is available in the form of reflected or
transmitted
• Analog image processing is an area that deals with
the processing of analog electrical signals using
analog circuits. The imaging systems that use film for
recording images are also known as analog imaging
systems.

What is Digital Image Processing?
• Digital image processing is an area that uses
digital circuits, systems, and software
algorithms to carry out the image processing
operations. The image processing operations
may include quality enhancement of an
image, counting of objects, and image
analysis.

Reasons for Popularity of DIP
1. It is easy to post-process the image. Small corrections can
be made in the captured image using software.
2. It is easy to store the image in the digital memory.
3. It is possible to transmit the image over networks. So
sharing an image is quite easy.
4. A digital image does not require any chemical process. So it
is very environment friendly, as harmful film chemicals are
not required or used.
5. It is easy to operate a digital camera.

IMAGE PROCESSING AND RELATED
FIELDS

Relations with other branches
• Image processing deals with raster data or bitmaps, whereas
computer graphics primarily deals with vector data.
• In digital signal processing, one often deals with the
processing of a one-dimensional signal. In the domain of
image processing, one deals with visual information that is
often in two or more dimensions.

• The main goal of machine vision is to interpret the image and
to extract its physical, geometric, or topological properties.
Thus, the output of image processing operations can be
subjected to more techniques, to produce additional
information for interpretation.

• Image processing is about still images. Thus, video processing
is an extension of image processing. In addition, images are
strongly related to multimedia, as the field of multimedia
broadly includes the study of audio, video, images, graphics,
and animation.

• Optical image processing deals with lenses, light, lighting
conditions, and associated optical circuits. The study of lenses
and lighting conditions has an important role in the study of
image processing.

• Image analysis is an area that concerns the extraction and
analysis of object information from the image. Imaging
applications involve both simple statistics such as counting
and mensuration and complex statistics such as advanced
statistical inference. So statistics play an important role in
imaging applications.

Digital Image
An image can be defined as a 2D signal that varies over
the spatial coordinates x and y, and can be written
mathematically as f (x, y).

Digital Image
• The value of the function f (x, y) at every point indexed by a
row and a column is called grey value or intensity of the
image.
• Resolution is an important characteristic of an imaging
system. It is the ability of the imaging system to produce the
smallest discernable details, i.e., the smallest sized object
clearly, and differentiate it from the neighbouring small
objects that are present in the image.

Useful definitions
• Image resolution depends on two factors—optical resolution
of the lens and spatial resolution.
• A useful way to define resolution is the smallest number of
line pairs per unit distance.
• Spatial resolution depends on two parameters—
1. The number of pixels of the image
2. The number of bits necessary for adequate intensity
resolution, referred to as the bit depth.

Useful definitions
• The number of bits necessary to encode the pixel
value is called bit depth. Bit depth is a power of two;
it can be written as powers of 2.
• So the total number of bits necessary to represent
the image is
• Number of rows = Number of columns * Bit depth

Classification of Images

Based on Nature
• Natural Images
Produced by Cameras and Scanners
• Synthetic Images
Produced by Computer Programs

Based on Attributes
• Raster Images
Pixel based Images
• Vector Images
Produced by Geometrical attributes like
Lines, circles etc

Types of Images Based on Colour
Grey scale images are different from binary
images as they have many shades of grey
between black and white. These images are
also called monochromatic as there is no
colour component in the image, like in binary
images. Grey scale is the term that refers to
the range of shades between white and black
or vice versa.

Types of Images
• In binary images, the pixels assume a value of 0 or 1.
So one bit is sufficient to represent the pixel value.
Binary images are also called bi-level images.
• In true colour images, the pixel has a colour that is
obtained by mixing the primary colours red, green,
and blue. Each colour component is represented like
a grey scale image using eight bits. Mostly, true
colour images use 24 bits to represent all the
colours.

Indexed Image
• A special category of colour images is the indexed
image. In most images, the full range of colours is not
used. So it is better to reduce the number of bits by
maintaining a colour map, gamut, or palette with the
image.

Storage Structure

Pseudocolour Image
• Like true colour images, Pseudocolour images are
also used widely in image processing. True colour
images are called three-band images. However, in
remote sensing applications, multi-band images or
multi-spectral images are generally used. These
images, which are captured by satellites, contain
many bands.

Example Problems

Types of Images based on Dimensions
• Types of Images Based on Dimensions
2D and 3D
• Types of Images Based on Data Types
• Single, double, Signed or unsigned.

Types of Images based on Data types
• Single, float, double, Signed , Logical or
unsigned.

Types of Images based on Domain
Specific Images
• Range Images
• Pixel value denotes the distance between
• camera and object
• Multispectral Images
• Many band images encountered in remote
• sensing

DIGITAL IMAGE PROCESSING
OPERATIONS

Image Analysis

Image Enhancement

Image Restoration

Image Compression

Image Synthesis

Image Processing Applications

Based on Electromagnetic Spectrum
• Radio Waves
Magnetic Resonance Imaging
• Microwave
Radar Imaging (Radio Detection and
Ranging)
SAR Imaging (Synthetic Aperture
Imaging)
• Infrared Waves
• Visible Light
• Ultraviolet ray
• Gamma Rays
• Ultrasound Imaging

Survey Based on Application
• Pattern Recognition
Fingerprint, face, Iris, DNA

Medical Imaging
• Visualization and Rendering

More Domains
• Remote Sensing
• Image communication
• Image Security and Copyright Protection

More Domains
• Video Processing
• Image Understanding
• Military Applications
• Computational Photography and Photography
• Image and Video Analytics
• Image Security and Copyright Protection

Image Effects

Image Mosaicking

More Domains
• Entertainment
• Image retrieval Systems

image processing image enhancement and filtering

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