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.
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).
20. 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.
22. This Paper has been submitted under the guidance of
K. Megala B.E – Lecturer (Computer Engg).
M.Saravanan (M.E) – Lecturer (Computer Engg).
Over headed by
Mr.M. Ramesh Kumar, MCA.,Mphil
(Computer Engg).
24. BIBLIOGRAPHY
John C. Ross. Image Processing Hand book, CRC Press. 1994.
[2] Peter Mc Curry, Fearghal Morgan, Liam Kilmartin. Xilinx FPGA
implementation of a pixel processor for object detection applications. In the
Proc. Irish Signals and Systems Conference, Volume 3, Page(s):346 – 349,
Oct. 2001.
[3] M. Moore. A DSP-based real time image processing system. In the
Proceedings of the 6th International conference on signal processing
applications and technology, Boston MA, August 1995.
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