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1. 6 Weeks / Months Industrial Training
On
MATLAB
PHAGWARA | JALANDHAR | CHANDIGARH
Contact : +91 9041262727, 9779363902
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3. • INTRODUCTION
• ACQUIRING IMAGES
– HUMAN RELIANCE ON IMAGES FOR
INFORMATION
– ELECTRONICS AND BANDWIDTH
LIMITATIONS
– HIGH RESOLUTION IMAGING
– COLOR IMAGING
– COLOR SPACES
– COLOR DISPLAYS
– IMAGE TYPES
• ITS TIME FOR DEMO
• CONCLUSION
• BIBLIOGRAPHY

4. Image processing involves processing or
altering an existing image in a desired manner.
The next step is obtaining an image in a
readable format.
The Internet and other sources provide
countless images in standard formats.

5. Image processing are of two aspects..
improving the visual appearance of images
to a human viewer
preparing images for measurement of the
features and structures present.

6. Since the digital image is “invisible” it must be prepared
for viewing on one or more output device (laser
printer,monitor,etc)
The digital image can be optimized for the application by
enhancing or altering the appearance of structures within
it (based on: body part, diagnostic task, viewing
preferences,etc)
It might be possible to analyze the image in the
computer and provide cues to the radiologists to help
detect important/suspicious structures (e.g.: Computed
Aided Diagnosis, CAD)

7. Scientific instruments commonly produce images
to communicate results to the operator, rather
than generating an audible tone or emitting a
smell.
Space missions to other planets and Comet Halley
always include cameras as major components, and
we judge the success of those missions by the
quality of the images returned.

8. Image-to-image transformations
Image-to-information transformations
Information-to-image transformations

9. Enhancement (make image more useful, pleasing)
Restoration
Egg. deblurring ,grid line removal
Geometry
(scaling, sizing , Zooming, Morphing one object to
another).

10. Image statistics (histograms)
Histogram is the fundamental tool for analysis and image processing
Image compression
Image analysis (image segmentation, feature extraction,
pattern recognition)
computer-aided detection and diagnosis (CAD)

11. Decompression of compressed image data.
Reconstruction of image slices from CT or MRI raw data.
Computer graphics, animations and virtual reality (synthetic objects).

12. The process of obtaining an high resolution (HR) image or a
sequence of HR images from a set of low resolution (LR)
observations.
HR techniques are being applied to a variety of fields, such
as obtaining
improved still images
high definition television,
high performance color liquid crystal display (LCD) screens,
video surveillance,
remote sensing, and
medical imaging.

13. Conversion from RGB (the brightness of the individual red, green, and
blue signals at defined wavelengths) to YIQ/YUV and to the other color
encoding schemes is straightforward and loses no information.
Y, the “luminance” signal, is just the brightness of a panchromatic
monochrome image that would be displayed by a black-and-white
television receiver

14. Most computers use color monitors that have much
higher resolution than a television set but operate on
essentially the same principle.
Smaller phosphor dots, a higher frequency scan, and
a single progressive scan (rather than interlace)
produce much greater sharpness and color purity.

15. Digital processing requires images to be obtained in the
form of electrical signals. These signals can be digitized into
sequences of numbers which then can be processed by a
computer. There are many ways to convert images into
digital numbers. Here, we will focus on video technology, as
it is the most common and affordable approach.

16. Multiple images may constitute a series of views of the
same area, using different wavelengths of light or other
signals.
Examples include the images produced by satellites, such as
– the various visible and infrared wavelengths recorded by the
Landsat Thematic Mapper(TM), and
– images from the Scanning Electron Microscope (SEM) in which
as many as a dozen different elements may be represented by
their X-ray intensities.
These images may each require processing.

17. A general-purpose computer to be useful for image
processing, four key demands must be met: high-
resolution image display, sufficient memory transfer
bandwidth, sufficient storage space, and sufficient
computing power.
A 32-bit computer can address
up to 4GB of memory(RAM).

18. Adobe Photoshop
Corel Draw
Serif Photoplus

19. In electrical engineering and computer science, image
processing is any form of signal processing for which the
input is an image, such as photographs or frames of video;
the output of image processing can be either an image or a
set of characteristics or parameters related to the image.
Most image-processing techniques involve treating the
image as a two-dimensional signal and applying standard
signal-processing techniques to it.

20. “Things that think…
don’t make sense unless they link.”

21. Opp. Bus Stand, Parmar Complex
Backside Axis Bank, Phagwara
Punjab – INDIA.
Cont: +91 9041262727, 9779363902
Web: www.e2matrix.com
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