06-04-2011, 04:21 PM
[attachment=11808]
DIGITAL IMAGE PROCESSING
Abstract
By using Digital Image Processing we enhance the digital images and extracting information and features from the image. Digital Image Processing has become the most common form of image processing, and it is generally used because it is not only the most versatile method, but also the cheapest. This is one type of image processing and it used for editing the digital images which are taken from the digital cameras. This technology is more useful in the investigation in Crime Branch. Digital Image Processing has the advantages as a wider range of algorithm to be applied to the input data and can avoid the problems such as build-up of notice and signal distortion during processing. For this the NASA and WE military have developed advanced computer software. By using this software improve the clarity of and amount of detail visible in still and video images.
The main feature of this technology is Digital Image Editing. Image Editors are provide the means for altering and improving images in an all most endless number of time. They accept images in large variety of image formats. The other features of this technology are Image Size Alteration, Cropping on Image, Removal of Notice and unwanted elements, merging of images and finally color adjustments.
And in this paper we present categories of digital image processing, Image Compression, Image viewing and image types, and digital image editing, and finally advantages and disadvantages of digital image processing.
Introduction
Digital Image Processing is concerned with acquiring and processing of an image. In simple words an image is a representation of a real scene, either in black and white or in color, and either in print form or in a digital form i.e., technically a image is a two-dimensional light intensity function. In other words it is a data intensity values arranged in a two-dimensional form like an array, the required property of an image can be extracted from processing an image. Image is typically by stochastic models. It is represented by AR model. Degradation is represented by MA model.
Image Processing
Image processing is enhancing image or extracting information or features from an image. Any activity that transforms an input image into an output image. The manipulation and alteration of images using computer software.
Digital Image Processing
Digital image processing is the use of computer to perform on. Digital image processing has the same advantages (over analog image processing) as has (over analog signal 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.
Digital Image
A digital image is a representation of a two-dimensional a finite set of values, called picture elements or. Typically, the pixels are stored in computer memory as one or a two-dimensional array of small integers. These values are often transmitted or stored in a form.
Digital images can be by a variety of input devices and techniques, such as, scanners, coordinate-measuring machines, seismographic profiling, airborne radar, and more.
It is an image that was acquired through scanners or captured from digital cameras. The most common kind of digital image processing is digital image editing.
History
Because of the computational load of dealing with images containing millions of pixels, digital image processing was largely of academic interest until the 1970s, when dedicated hardware became available that could process images in real time, for some dedicated problems such as television standards conversion. As general-purpose computers became faster, they started to take over the role of dedicated hardware for all but the most specialized and compute-intensive operations.
With the fast computers and signal processors available in the 2000s, digital image processing has become the most common form of image processing, and is generally used because it is not only the most versatile method, but also the cheapest.
Digital Processing Of Camera Images
Images taken by popular digital cameras often need processing to improve their quality; distinct advantage digital cameras have over film cameras. The digital image processing is done by special software programs that manipulate the images is many ways. This process is performed in a "digital darkroom", which is not really a darkroom as it is accomplished via a computer and keyboard.
Reasons for Introducing Digital Image Processing
Figure 1: Polarization by filters
Few types of evidence are more incriminating than a photograph or videotape that places a suspect at a crime scene, whether or not it actually depicts the suspect committing a criminal act. Ideally, the image will be clear, with all persons, settings, and objects reliably identifiable. Unfortunately, though, that is not always the case, and the photograph or video image may be grainy, blurry, of poor contrast, or even damaged in some way.
In such cases, investigators may rely on computerized technology that enables digital processing and enhancement of an image. The U.S. government, and in particular, the military, the FBI, and the National Aeronautics and Space Agency (NASA), and more recently, private technology firms, have developed advanced computer software that can dramatically improve the clarity of and amount of detail visible in still and video images. NASA, for example, used digital processing to analyze the video of the Challenger incident.
How Can We Process An Image?
The first step in digital image processing is to transfer an image to a computer, digitizing the image and turning it into a computer image file that can be stored in a computer's memory or on a storage medium such as a hard disk or CD-ROM. Digitization involves translating the image into a numerical code that can be understood by a computer. It can be accomplished using a scanner or a video camera linked to a frame grabber board in the computer.
The computer breaks down the image in to thousands of pixels. Pixels are the smallest component of an image. They are the small dots in the horizontal lines across a television screen. Each pixel is converted into a number that represents the brightness of the dot. For a black-and-white image, the pixel represents different shades between total black and full white. The computer can then adjust the pixels to enhance image quality.
Categories Of Digital Image Processing:
The Three main categories of digital image processing are:
Image Compression is a mathematical technique used to reduce the amount of computer memory needed to store a digital image. The computer discards (rejects) some information, while retaining sufficient information to make the image pleasing to the human eye.
Enhancement Image enhancement techniques can be used to modify the brightness and contrast of an image, to remove blurriness, and to filter out some of the noise. Using mathematical equations called algorithms, the computer applies each change to either the whole image or targets a particular portion of the image.
For example, global contrast enhancement would affect the entire image, whereas local contrast enhancement would improve the contrast of small details, such as a face or a license plate on a vehicle. Some algorithms can remove background noise without disturbing the key components of the image.
Measurement Extraction is used to gather useful information from an enhanced image.
Image Viewing
The user can utilize different program to see the image. The GIF, JPEG and PNG images can be seen simply using a web browser because they are the standard internet image formats. The SVG format is more and more used in the web and is a standard W3C format.
Image Types
Digital images can be classified according to the number and nature of those samples: The term digital image is also applied to data associated to points scattered over a three-dimensional region, such as produced by tomography equipment. In that case, each datum is called a voxel.
Types Of Images
1. Binary Image: A binary image is a digital image that has only two possible values for each pixel. Binary images are also called bi-level or two-level. A binary image is usually stored in memory as a bitmap, a packed array of bits. A binary image is also a compiled version of source code in Linux and Unixes
2. Gray Scale: In computing, a grayscale or grayscale digital image is an image in which the value of each pixel is a single sample. Grayscale images are distinct from black-and-white images, which in the context of computer imaging are images with only two colors, black and white; grayscale images have many shades of gray in between. In most contexts other than digital imaging, however, the term "black and white" is used in place of "grayscale";
For example, photography in shades of gray is typically called "black-and-white photography". The term monochromatic in some digital imaging contexts is synonymous with grayscale, and in some contexts synonymous with black-and-white.
3. Color Image: A (digital) color image is a digital image that includes color information for each pixel. For visually acceptable results, it is necessary (and almost sufficient) to provide three samples (color channels) for each pixel, which are interpreted as coordinates in some color space. The RGB color space is commonly used in computer displays, but other spaces such as YUV, HSV, and are often used in other contexts. Color Image Representation: A color image is usually stored in memory as a raster map, a two-dimensional array of small integer triplets; or (rarely) as three separate raster maps.
DIGITAL IMAGE PROCESSING
Abstract
By using Digital Image Processing we enhance the digital images and extracting information and features from the image. Digital Image Processing has become the most common form of image processing, and it is generally used because it is not only the most versatile method, but also the cheapest. This is one type of image processing and it used for editing the digital images which are taken from the digital cameras. This technology is more useful in the investigation in Crime Branch. Digital Image Processing has the advantages as a wider range of algorithm to be applied to the input data and can avoid the problems such as build-up of notice and signal distortion during processing. For this the NASA and WE military have developed advanced computer software. By using this software improve the clarity of and amount of detail visible in still and video images.
The main feature of this technology is Digital Image Editing. Image Editors are provide the means for altering and improving images in an all most endless number of time. They accept images in large variety of image formats. The other features of this technology are Image Size Alteration, Cropping on Image, Removal of Notice and unwanted elements, merging of images and finally color adjustments.
And in this paper we present categories of digital image processing, Image Compression, Image viewing and image types, and digital image editing, and finally advantages and disadvantages of digital image processing.
Introduction
Digital Image Processing is concerned with acquiring and processing of an image. In simple words an image is a representation of a real scene, either in black and white or in color, and either in print form or in a digital form i.e., technically a image is a two-dimensional light intensity function. In other words it is a data intensity values arranged in a two-dimensional form like an array, the required property of an image can be extracted from processing an image. Image is typically by stochastic models. It is represented by AR model. Degradation is represented by MA model.
Image Processing
Image processing is enhancing image or extracting information or features from an image. Any activity that transforms an input image into an output image. The manipulation and alteration of images using computer software.
Digital Image Processing
Digital image processing is the use of computer to perform on. Digital image processing has the same advantages (over analog image processing) as has (over analog signal 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.
Digital Image
A digital image is a representation of a two-dimensional a finite set of values, called picture elements or. Typically, the pixels are stored in computer memory as one or a two-dimensional array of small integers. These values are often transmitted or stored in a form.
Digital images can be by a variety of input devices and techniques, such as, scanners, coordinate-measuring machines, seismographic profiling, airborne radar, and more.
It is an image that was acquired through scanners or captured from digital cameras. The most common kind of digital image processing is digital image editing.
History
Because of the computational load of dealing with images containing millions of pixels, digital image processing was largely of academic interest until the 1970s, when dedicated hardware became available that could process images in real time, for some dedicated problems such as television standards conversion. As general-purpose computers became faster, they started to take over the role of dedicated hardware for all but the most specialized and compute-intensive operations.
With the fast computers and signal processors available in the 2000s, digital image processing has become the most common form of image processing, and is generally used because it is not only the most versatile method, but also the cheapest.
Digital Processing Of Camera Images
Images taken by popular digital cameras often need processing to improve their quality; distinct advantage digital cameras have over film cameras. The digital image processing is done by special software programs that manipulate the images is many ways. This process is performed in a "digital darkroom", which is not really a darkroom as it is accomplished via a computer and keyboard.
Reasons for Introducing Digital Image Processing
Figure 1: Polarization by filters
Few types of evidence are more incriminating than a photograph or videotape that places a suspect at a crime scene, whether or not it actually depicts the suspect committing a criminal act. Ideally, the image will be clear, with all persons, settings, and objects reliably identifiable. Unfortunately, though, that is not always the case, and the photograph or video image may be grainy, blurry, of poor contrast, or even damaged in some way.
In such cases, investigators may rely on computerized technology that enables digital processing and enhancement of an image. The U.S. government, and in particular, the military, the FBI, and the National Aeronautics and Space Agency (NASA), and more recently, private technology firms, have developed advanced computer software that can dramatically improve the clarity of and amount of detail visible in still and video images. NASA, for example, used digital processing to analyze the video of the Challenger incident.
How Can We Process An Image?
The first step in digital image processing is to transfer an image to a computer, digitizing the image and turning it into a computer image file that can be stored in a computer's memory or on a storage medium such as a hard disk or CD-ROM. Digitization involves translating the image into a numerical code that can be understood by a computer. It can be accomplished using a scanner or a video camera linked to a frame grabber board in the computer.
The computer breaks down the image in to thousands of pixels. Pixels are the smallest component of an image. They are the small dots in the horizontal lines across a television screen. Each pixel is converted into a number that represents the brightness of the dot. For a black-and-white image, the pixel represents different shades between total black and full white. The computer can then adjust the pixels to enhance image quality.
Categories Of Digital Image Processing:
The Three main categories of digital image processing are:
Image Compression is a mathematical technique used to reduce the amount of computer memory needed to store a digital image. The computer discards (rejects) some information, while retaining sufficient information to make the image pleasing to the human eye.
Enhancement Image enhancement techniques can be used to modify the brightness and contrast of an image, to remove blurriness, and to filter out some of the noise. Using mathematical equations called algorithms, the computer applies each change to either the whole image or targets a particular portion of the image.
For example, global contrast enhancement would affect the entire image, whereas local contrast enhancement would improve the contrast of small details, such as a face or a license plate on a vehicle. Some algorithms can remove background noise without disturbing the key components of the image.
Measurement Extraction is used to gather useful information from an enhanced image.
Image Viewing
The user can utilize different program to see the image. The GIF, JPEG and PNG images can be seen simply using a web browser because they are the standard internet image formats. The SVG format is more and more used in the web and is a standard W3C format.
Image Types
Digital images can be classified according to the number and nature of those samples: The term digital image is also applied to data associated to points scattered over a three-dimensional region, such as produced by tomography equipment. In that case, each datum is called a voxel.
Types Of Images
1. Binary Image: A binary image is a digital image that has only two possible values for each pixel. Binary images are also called bi-level or two-level. A binary image is usually stored in memory as a bitmap, a packed array of bits. A binary image is also a compiled version of source code in Linux and Unixes
2. Gray Scale: In computing, a grayscale or grayscale digital image is an image in which the value of each pixel is a single sample. Grayscale images are distinct from black-and-white images, which in the context of computer imaging are images with only two colors, black and white; grayscale images have many shades of gray in between. In most contexts other than digital imaging, however, the term "black and white" is used in place of "grayscale";
For example, photography in shades of gray is typically called "black-and-white photography". The term monochromatic in some digital imaging contexts is synonymous with grayscale, and in some contexts synonymous with black-and-white.
3. Color Image: A (digital) color image is a digital image that includes color information for each pixel. For visually acceptable results, it is necessary (and almost sufficient) to provide three samples (color channels) for each pixel, which are interpreted as coordinates in some color space. The RGB color space is commonly used in computer displays, but other spaces such as YUV, HSV, and are often used in other contexts. Color Image Representation: A color image is usually stored in memory as a raster map, a two-dimensional array of small integer triplets; or (rarely) as three separate raster maps.
