1. In sensing, two elements are required to acquire digital images. The first is physical device that is sensitive to the energy radiated by the object we wish to image. The second called a digitizer, is a device for converting the output of the physical sensing device into digital form.
2. Specialized image processing hardware usually consists fo the digitizer plus hardware that performs other primitive operations such as arithmetic and logical operations (ALU). Eg. Noise reduction. This type of hardware sometimes is called a fron end subsystem.
3. The computer is an image processing system is a general purpose to supercomputer
4. Software which include image processing specialized modules tha tperforma specific tasks
5. Mass storage capability is a must in image processing applications.
6. Image displays in use today are mainly color tv monitors.
7. hardcopy devices for recording images include laser printers, film cameras, inkjet units and cdrom
8. Networking for communication
Monday, June 29, 2009
Fundamental steps in digital image processing
1. Image acquisition is the first process. Generally the image acquisition stage involves preprocessing such as scaling.
2. Image enhancement is among the simplest and most area. The idea behind enhancement techniques is to bring out detail that is obscured or simply to highlight certain features of interest in an image.
3. Image restoration is ain area that also deals with improving the appearance of an image. Unlike enhancement, which is subjective, image restoration is objective. Image restoration techniques tend to be based on mathematical or probabilistic models of image degradation. Enhancement on the other hand, is based on human subjective preferences regarding what constitutes a good enhancement result
4. Color image processing
5. Wavelets are the foundation for representing images in various degrees of resolution.
6. Compression deals with techniques for reducing the storage required to save an image or the bandwidth required to transmit it.
7. Morphological processing deals with tools for extracting image components that are useful in the representation and description of shape.
8. Segmentation procedures partition an image into its constituent parts or objects.
9. Representation and description almost always follow the output of a segmentation stage, which usually is raw pixel data, constituting either the boundary of a region. Representation first deals with whether the data should be represented as a boundary or as a complete region. Choosing representation is only part of the solution for transformation raw data into a form suitable for subsequent computer processing. A method must also be specified for describe the data so that features of interest are highlighted. Description or feature slection deals with extracting attributes that result in some quantitative information of interest or are basic for differentiation one class of objects from another.
10. Object recognization
2. Image enhancement is among the simplest and most area. The idea behind enhancement techniques is to bring out detail that is obscured or simply to highlight certain features of interest in an image.
3. Image restoration is ain area that also deals with improving the appearance of an image. Unlike enhancement, which is subjective, image restoration is objective. Image restoration techniques tend to be based on mathematical or probabilistic models of image degradation. Enhancement on the other hand, is based on human subjective preferences regarding what constitutes a good enhancement result
4. Color image processing
5. Wavelets are the foundation for representing images in various degrees of resolution.
6. Compression deals with techniques for reducing the storage required to save an image or the bandwidth required to transmit it.
7. Morphological processing deals with tools for extracting image components that are useful in the representation and description of shape.
8. Segmentation procedures partition an image into its constituent parts or objects.
9. Representation and description almost always follow the output of a segmentation stage, which usually is raw pixel data, constituting either the boundary of a region. Representation first deals with whether the data should be represented as a boundary or as a complete region. Choosing representation is only part of the solution for transformation raw data into a form suitable for subsequent computer processing. A method must also be specified for describe the data so that features of interest are highlighted. Description or feature slection deals with extracting attributes that result in some quantitative information of interest or are basic for differentiation one class of objects from another.
10. Object recognization
Examples of fields that use digital image processing
One of the simplest ways to develop a basic understanding of the extent of image processing applications is to categories images according to their source (e.g., visual, x-ray and son on). The principle energy source for images in use today is the electromagnetic energy spectrum. Other important sources of energy include acoustic, ultrasonic and electronic (in the form of electron beams used in electron microscopy). Synthetic images used for modeling and visualization are generated by computer.
Electromagnetic waves can be conceptualized as propagating sinusoidal waves of varying wavelengths, or they can be thought of as a stream of mass less particles, each traveling in a wavelike pattern and moving at the speed of light. Each mass less particle contain a certain amount (bundle ) of energy. Each bundle of energy is called a photon. If spectral bands are grouped according to energy per photon, we obtain the spectrum ranging from gamma rays (highest energy) at the one end to radio waves (lowest energy) at the other.
Gammaray imaging
Major uses of imaging based on gamma rays include nuclear medicine and astronomical observations. In nuclear medicine, the approach is to inject a patient with a radioactive isotope that emits gamma rays as it decays. Images are produced from emissions collected by gamma ray detectors.
Positron emission tomography(PET)
The patient is given a radioactive isotope that emits positrons as it decays. When a positron meets a electron, both are annihilated and two gamma rays are given off. These are detected and a tomographic image is created using the basic principles of tomography.
X-ray Imaging (oldest source of EM radiation)
X-rays for medical and industrial imaging are generated using an x-ray tube, which is a vacuum tube with a cathode and anode. The cathode is heated, causing free electrons to be released. These electrons flow at high speed to the positively charged anode. When the electron strike a nucleus, energy is released in the form x-ray radiation. The energy(penetrating power) of the x-rays is controlled by a current applied to the filament in the cathode.
Angiography is another major application in an area called contrast enhancement radiography. The procedure is used to obtain images of blodd vessels. A catheter ( a small flexible hollow tube) is inserted, for example into an artery of vein in the groin. The catheter is threaded into the blood vessel and guided to the area to be studied. When the catheter reaches the site under investigation, an x-ray contrast medium is injected through the catheter. This enhances contrast of the blood vessles and enables the radiologist to see any irregularities or blockages.
Imaging in the visible and infrared bands
Infrared band often is used in conjunction with visual imaging. The applications ranges from light microscopy, astronomy, remote sensing industry and law enforcement.
Eg:
Microscopy- the applications ranges from enhancement to measurement
Remote sensing-weather observation from multispectral images from satellites
Industry-check up the bottledrink with less quantity
Law enforcement – biometrics
Imaging in the microwave band
Dominant application in microwave band is radar. The unique feature of imaging radar is its ability to collect data over virtually any region at any time, regardless of weather or ambient lighting conditions. Some radar waves can penetrate clouds and under certain conditions can also see through vegetation, ice and extremely dry sand. In many cases, radar is the only way to explore inaccessible regions of the earth’s surface. An imaging radar works like a flash camera in that it provides it own illumination (microwaves pulses) to illuminate an area on the ground and take a snapshot image.
Imaging in the radio band
Major applications of imaging in the radio band are in medicine and astronomy. In medicine radio waves are used in magnetic resonance imaging (MRI). This techniques places a patient in a powerful magnet and passes radio waves through his or her body in short pulses. Each pulse causes a responding pulse of radio waves to be emitted by patient’s tissues. The location from which theses signals orginate and their strength are determined by a computer which produces a two-dimensional picture of a section of the patient.
Other Imaging Modalities Acoustic images, electron microscopy and synthetic (computer – generated images)
Imaging using sound finds application in geological exploration, industry and medicine. The most important commercial applications of image processing in geology are in mineral and oil exploration.
Ultrasound imaging is used routinely in manufacturing, the best known applications of this technique are in medicine, especially in obsterics, where unborn babies are imaged to determine the health of their development.
Fractals are striking examples of computer-generated images.
Electromagnetic waves can be conceptualized as propagating sinusoidal waves of varying wavelengths, or they can be thought of as a stream of mass less particles, each traveling in a wavelike pattern and moving at the speed of light. Each mass less particle contain a certain amount (bundle ) of energy. Each bundle of energy is called a photon. If spectral bands are grouped according to energy per photon, we obtain the spectrum ranging from gamma rays (highest energy) at the one end to radio waves (lowest energy) at the other.
Gammaray imaging
Major uses of imaging based on gamma rays include nuclear medicine and astronomical observations. In nuclear medicine, the approach is to inject a patient with a radioactive isotope that emits gamma rays as it decays. Images are produced from emissions collected by gamma ray detectors.
Positron emission tomography(PET)
The patient is given a radioactive isotope that emits positrons as it decays. When a positron meets a electron, both are annihilated and two gamma rays are given off. These are detected and a tomographic image is created using the basic principles of tomography.
X-ray Imaging (oldest source of EM radiation)
X-rays for medical and industrial imaging are generated using an x-ray tube, which is a vacuum tube with a cathode and anode. The cathode is heated, causing free electrons to be released. These electrons flow at high speed to the positively charged anode. When the electron strike a nucleus, energy is released in the form x-ray radiation. The energy(penetrating power) of the x-rays is controlled by a current applied to the filament in the cathode.
Angiography is another major application in an area called contrast enhancement radiography. The procedure is used to obtain images of blodd vessels. A catheter ( a small flexible hollow tube) is inserted, for example into an artery of vein in the groin. The catheter is threaded into the blood vessel and guided to the area to be studied. When the catheter reaches the site under investigation, an x-ray contrast medium is injected through the catheter. This enhances contrast of the blood vessles and enables the radiologist to see any irregularities or blockages.
Imaging in the visible and infrared bands
Infrared band often is used in conjunction with visual imaging. The applications ranges from light microscopy, astronomy, remote sensing industry and law enforcement.
Eg:
Microscopy- the applications ranges from enhancement to measurement
Remote sensing-weather observation from multispectral images from satellites
Industry-check up the bottledrink with less quantity
Law enforcement – biometrics
Imaging in the microwave band
Dominant application in microwave band is radar. The unique feature of imaging radar is its ability to collect data over virtually any region at any time, regardless of weather or ambient lighting conditions. Some radar waves can penetrate clouds and under certain conditions can also see through vegetation, ice and extremely dry sand. In many cases, radar is the only way to explore inaccessible regions of the earth’s surface. An imaging radar works like a flash camera in that it provides it own illumination (microwaves pulses) to illuminate an area on the ground and take a snapshot image.
Imaging in the radio band
Major applications of imaging in the radio band are in medicine and astronomy. In medicine radio waves are used in magnetic resonance imaging (MRI). This techniques places a patient in a powerful magnet and passes radio waves through his or her body in short pulses. Each pulse causes a responding pulse of radio waves to be emitted by patient’s tissues. The location from which theses signals orginate and their strength are determined by a computer which produces a two-dimensional picture of a section of the patient.
Other Imaging Modalities Acoustic images, electron microscopy and synthetic (computer – generated images)
Imaging using sound finds application in geological exploration, industry and medicine. The most important commercial applications of image processing in geology are in mineral and oil exploration.
Ultrasound imaging is used routinely in manufacturing, the best known applications of this technique are in medicine, especially in obsterics, where unborn babies are imaged to determine the health of their development.
Fractals are striking examples of computer-generated images.
Friday, June 26, 2009
Digital Image Representation
An image can be defined as f(x,y) where x,y is the spatial co-ordinatess and amplitude is the intensity of the image at that point. The term gray level is used often to refer to the intensity of the monochrome images. Color images are formed by a combination of individual 2-D images. For eg in the RGB color system, a color image consists of three (red, green, blue) individual component images. For this reason, many of the techniques developed for monochrome images can be extended to color images by processing the the three component images individually.
Digitizing the corordinate values is called as sampling, digitizing the amplitude values is called quantization. When x,y and the amplitude values of f are all finite, discrete quantities we call the image a digital image.
The result of sampling and quantization is a matrix of real numbers. Assume that an image f(x,y) is sampled so that the resulting image has M rows and N columns. We say that the image is of size M * N. The values of the coordinates (x, y) are discrete quantities.
A 1*N matrix is called as row vector, where as M*1 matrix is called a column vector. A 1*1 matrix is scalar.
Digitizing the corordinate values is called as sampling, digitizing the amplitude values is called quantization. When x,y and the amplitude values of f are all finite, discrete quantities we call the image a digital image.
The result of sampling and quantization is a matrix of real numbers. Assume that an image f(x,y) is sampled so that the resulting image has M rows and N columns. We say that the image is of size M * N. The values of the coordinates (x, y) are discrete quantities.
A 1*N matrix is called as row vector, where as M*1 matrix is called a column vector. A 1*1 matrix is scalar.
Thursday, June 25, 2009
What is Digital image processing
An image may be defined as a two dimensional function, f(x,y), where x and y are spatial coorindates, and the amplitude of f at any pair of coordinatores (x,y) is called the intensity or gray level of the image at that point. When x,y and the amplitude values of f are all finite, discrete quanitites, we call the image a digital image. A digital image is composed of a finite number fo elements, each of which has a particular location and value. These elements are referred to as picture elements,image elements, pels and pixels. Pixel is the most widely used term.
Unlike humans, who are limited to the visual band of the electromagnetic (EM) spectrum, imaging machines cover almost the entire EM spectrum, ranging from gamma to radio waves. They can operate also on images generated by sources that humans are not accustomed to associating with images. These include ultrasound, electron microscopy and computer generated images. These include ultrasound, electron microscopy and computer generated images. Thus DIP encompases a wide and varied field of applications.
There are 3 type of computerized processes: Low-mid-high. Low level processes involve primitive operations such as reduce noise, contrast enhancement and image sharpening. Here both the input and output are images. Mid processes on images involve tasks such segmenetation (partitioning images into regions or objects), description of those objects to reduce them to a form suitable for computer processing and classification of individual objects. Here input is image but output is the attributes extracted from the images. High level involves "making sense " of an ensemble of recognized objects, as in image analysis, performing cognitive functions normally associated with human vision.
Unlike humans, who are limited to the visual band of the electromagnetic (EM) spectrum, imaging machines cover almost the entire EM spectrum, ranging from gamma to radio waves. They can operate also on images generated by sources that humans are not accustomed to associating with images. These include ultrasound, electron microscopy and computer generated images. These include ultrasound, electron microscopy and computer generated images. Thus DIP encompases a wide and varied field of applications.
There are 3 type of computerized processes: Low-mid-high. Low level processes involve primitive operations such as reduce noise, contrast enhancement and image sharpening. Here both the input and output are images. Mid processes on images involve tasks such segmenetation (partitioning images into regions or objects), description of those objects to reduce them to a form suitable for computer processing and classification of individual objects. Here input is image but output is the attributes extracted from the images. High level involves "making sense " of an ensemble of recognized objects, as in image analysis, performing cognitive functions normally associated with human vision.
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