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Module 1 digital image processing
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DIGITAL IMAGE PROCESSING
Module 1
Dr. Chetan H
CONTENT
What is a digital image?
What is digital image processing?
History of digital image processing
CONTENT
State the art examples of digital image processing.
Conclusion.
INTRODUCTION
- Digital image processing is the use of computer algorithms to perform image processing on digital images.
- As a subcategory or field of digital signal processing, digital image processing has many advantages over analog image processing.
- It allows a much wider range of algorithms to be applied to the input data and can avoid problems such as the build-up of noise and signal distortion during processing.
- Since images are defined over two dimensions (perhaps more) digital image processing may be modeled in the form of multidimensional systems.
INTRODUCTION
IMAGE PROCESSING SYSTEM
HISTOGRAMS
HISTOGRAMS
A digital image is a representation of a two dimensional image as a finite set of digital values, called picture element or pixel.
WHAT IS DIGITAL IMAGE?
PIXEL
PIXEL
Pixel value typically represent gray levels, colours, heights, opacities, etc.
Remember digitization implies that a digital image is an approximation of a real scene.
FORMATS
FORMATS:
Sample per point (B&W or Grayscale)
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Sample per point (Red, Green and Blue)
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Sample per point (Red, Green, Blue, and "Alpha", a.k.a. Opacity)
Digital image processing focus on two major tasks:
Improvement of pictorial information for human interpretation.
Processing of image data for storage, transmission and representation for autonomous machine perception
WHAT IS DIGITAL IMAGE PROCESSING?
Digital image processing allows the use of much more complex algorithms, and hence, can offer both more sophisticated performance at simple tasks, and the implementation of methods which would be impossible by analog means.
FUNDAMENTAL STEPS IN DIP
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HISTORY
Many of the techniques of digital image processing, or digital picture processing as it often was called, were developed in the 1960s at the Jet Propulsion Laboratory, with application to satellite imagery, wire-photo standards conversion, medical imaging, videophone, character recognition, and photograph enhancement. That changed in the 1970s, when digital image processing proliferated as cheaper computers and dedicated hardware became available.
With the fast computers and signal processors available in the 2000s, digital image processing has become the most common form of image processing and generally, is used because it is not only the most versatile method, but also the cheapest.
Digital image processing technology for medical applications was inducted into the Space Foundation Space Technology Hall of Fame in 1994.
In 2002 Raanan Fattel, introduced Gradient domain image processing, a new way to process images in which the differences between pixels are manipulated rather than the pixel values themselves.
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Intorduction
Radio waves
EM spectrum
Microwave
Infrared rays
Visible light
EM spectrum
UV rays
X rays
Gamma rays
Improvement of pictorial information for human interpretation and analysis.
Typical applications:
EXAMPLES
Noise Filtering
Content Enhancement
contrast enhancement
deblurring
Remote sensing
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CONCLUSION
In most cases, effective use of color space- face color relationships and morphological processing allowed effective pre-processing.
Summary
For images trained on, able to detect faces with reasonable accuracy and miss and false alarm rates.
Adaptive adjustment of template scale, angle, and threshold allowed most faces to be detected.
ANY QUESTIONS?