1. IMAGE PROCESSING
Presented by
G.Raga Deepthi(10H71F0032),IMCA
N.Geetha (10H71F0011),IMCA
Devineni Venkata Ramana & Dr.Hima Sekhar
MIC College of Technology
Kanchikacherla
INTRODUCTION
• 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.
• 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.
WHY DO WE NEED IMAGE PROCESSING?…
• 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).
ACQUIRING IMAGE…
• 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.
2. TYPES OF IMAGE PROCESSING
• Image-to-image transformations
• Image-to-information transformations
• Information-to-image transformations
IMAGE-TO-IMAGE TRANSFORMATIONS
• Enhancement (make image more useful, pleasing)
• Restoration
Egg. deblurring ,grid line removal
• Geometry
(scaling, sizing , Zooming, Morphing one object to another).
IMAGE-TO-INFORMATION TRANSFORMATIONS
• 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)
INFORMATION-TO-IMAGE TRANSFORMATIONS
• Decompression of compressed image data.
• Reconstruction of image slices from CT or MRI raw data.
3. • Computer graphics, animations and virtual reality (synthetic objects).
HIGH RESOLUTION IMAGING
• 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 imageshigh definition television, high performance color liquid
crystal display (LCD) screens, video surveillance, remote sensing, and medical
imaging.
COLOR SPACES
• 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 .
COLOR DISPLAYS
• Most computers use color monitors that have much higher resolution than a
television set but operate on essentially the same principle.
4. • Smaller phosphor dots, a higher frequency scan, and a single progressive
scan (rather than interlace) produce much greater sharpness and color purity.
IMAGE SENSORS
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.
MULTIPLE IMAGES
• 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.
HARDWARE REQUIREMENTS
• 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 sufficientcomputing power.
• A 32-bit computer can addressup to 4GB of memory(RAM).
5. SOFTWARE REQUIREMENTS
• Adobe Photoshop
• Corel Draw
• Serif Photoplus
CONCLUSION
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.