Digital and image signal processing techniques allow for manipulation of digital images through computers. Digital images are made up of pixels that can represent grayscale or color. Concepts like linearity, convolution, Fourier transforms, interpolation and sampling are used to analyze and extract information from multidimensional digital image signals. Common image processing techniques include representation, preprocessing like scaling and reduction, enhancement to accentuate features, analysis through quantitative measurements, and segmentation to subdivide images. Applications of digital image processing include agricultural monitoring through satellite imagery, production automation for quality control, disaster management using drone imagery, and medical imaging for diagnosis and surgery.

1. DIGITAL SIGNAL
PROCESSING
Submitted to:
Dr. Maheshwar R
Submitted by:
KUNAL RANA 18BEE10024

2. Digital Signal Processing:
● Signals can be defined as something that
conveys information. They are of two types: a)
Analog signal b) Digital signal
● Signal processing refers to Analyzing, modifying
and synthesizing the signals of get a desired
output.
● Analog signal can be converted into digital
signals by sampling or quantization.
● Analog signal is converted into discrete signal
and then it is converted into digital signal.
● Digital signal processing refers to analyzing
these digital signals to get the desired outputs.

3. Image Processing:
1. Image processing is a method to perform some operations on an image, in order to get an
enhanced image or to extract some useful information from it.
2. It is a type of signal processing in which input is an image and output may be image or
characteristics/features associated with that image.
3. Image processing basically includes the following three steps:
● Importing the image via image acquisition tools;
● Analysing and manipulating the image;
● Output in which result can be altered image or report that is based on image analysis.

4. Digital Image Processing:
● Digital image processing techniques help in manipulation of the digital images by using
computers. The three general phases while using digital technique are pre-processing,
enhancement, and display than Information is extracted.
● Digital Images are 2D signals that consist of picture elements called pixels. Each pixel can be
represented as x(m,n), where m is the row (height) , n is the column (width).
● Images can be of greyscale or colour type and we use DSP to split multidimensional signals and
extract each component. Concepts of linearity,convolution,fourier transform,interpolation and
sampling are used to achieve this.
● However new manipulations and specialized signals are generated to overcome limitations.

5. Image Processing
Techniques: • Image representation : Cartesian, support and image
representation of 2D signals called pixels.
• Image preprocessing : By Scaling, i.e, magnification of
image to have a closer view by magnifying or zooming
the interested part in the imagery. By reduction, bringing
the unmanageable size of data to a manageable limit. For
resampling an image.
• Image enhancement : To accentuate certain image
features for subsequent analysis or for image display.
• Image analysis : Making quantitative measurements
from an image to produce a description of it
• Image segmentation:The process that subdivides an
image into its constituent parts or objects.

6. Advantages of DIP:
● Image processing improves edge recognition, and when
combined with sub-pixel processing, reliable measurement
is consistently achieved.
● Higher speed
● Available in any desired format .
● Accuracy of measurement is even maintained when
monitoring curved, reflective surfaces where subtle
changes in colour.
● Images can be stored in the computer memory and easily
retrieved on the same computer screen.

7. Disadvantages of DIP:
● One of the principle disadvantages of
conventional binary processing, or grayscale
processing as it’s often known, has been the
inability of products to recognise contrast
effectively.
● The initial cost can be high depending on system
used .
● Once the system is damaged , images will be lost.

8. ● In Agricultural Landscape: Irrigation
monitoring and providing information can
be made possible by tracking satellite
imaging of the fields.Quality of yields can
be ensured by the reliable and accurate
method of image processing through sorting
and grading of fresh products.
APPLICATIONS OF
DIP:
Image processing technology extracts information from
images and integrates it for a wide range of applications.
● In Production Automation: Image
processing applications can make it
possible for machines to act as more
self-sufficient and ensure the quality
of products
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9. ● Disaster Management:Drone aircrafts
monitoring environmental and traffic
conditions can use image processing to
capture high resolution real-time videos
and photographs. monitoring the
progress and ensuring co-ordination
during such rescue operations can be
made easier with real-time image
processing techniques.
● Biomedical and Other Healthcare
Applications: 3D imaging and
rendering, doctors can see extremely
high quality 3D images of organs that
they couldn’t have seen otherwise. This,
in turn, can help them carry out delicate
surgeries and make accurate diagnoses.

10. THANK YOU.