Essay: Image processing

INTRODUCTION

1.1 IMAGE PROCESSING:

Image processing is a computer imaging where application involves a human being in the visual loop. In other words the image are to be examined and a acted upon by people.

The image processing mainly involves in three stages:

  • Image restoration.
  • Image enhancement.
  • Image compression.

1.1.1 Image Restoration

This is the process of taking an image with some known, or estimated degradation, and restoring it to its original appearance. Image restoration is often used in the field of photography or publishing where an image was somehow degraded but needs to be improved before it can be printed.

1.1.2 Image Enhancement

It involves taking an image and improving it visually, typically by taking advantages of human Visual Systems responses. One of the simplest enhancement techniques is to simply stretch the contrast of an image.

Enhancement methods tend to be problem specific. For example, a method that is used to enhance satellite images may not suitable for enhancing medical images. Although enhancement and restoration are similar in aim, to make an image look better. They differ in how they approach the problem. Restoration method attempt to model the distortion to the image and reverse the degradation, where enhancement methods use knowledge of the human visual systems responses to improve an image visually.

1.1.3 Image Compression

It involves reducing the typically massive amount of data needed to represent an image. This done by eliminating data that are visually unnecessary and by taking advantage of the redundancy that is inherent in most images. Image processing systems are used in many and various types of environments, such as:

1. Medical community

2. Computer ‘ Aided Design

 

3. Virtual Reality

4. Image Processing.

ABOUT GIS

A geographic information system (GIS) is a computer system designed to confine, stockpile, maneuver, examine, handle, and in attendance all types of geographical data. The acronym GIS is sometimes used for geographical information science or geospatial information studies to refer to the academic restraint or profession of functioning with geographic information systems and is a large domain inside the broader studious discipline of

Geoinformatics.

GIS can be forethought of since a system with the intent of spatial data entry, control, and salvage, scrutiny, and revelation functions. The completion of a GIS is often ambitious by jurisdictional (such as a city), rationale, or relevance requirements. Generally, a GIS execution may be custom-designed for an association. Hence, a GIS deployment developed for an function, jurisdiction, venture, or rationale may not be robotically interoperable or companionable with a GIS with the aim of has be developed for some other rationale, authority, venture, or rationale. What goes ahead of a GIS is a spatial data infrastructure, a notion that has no such preventive boundaries.

In a general sense, the phrase describe any in sequence system that integrate supplies, edit, analyze, share, and display geographic information for inform decision making. GIS application are tackle that tolerate users to craft interactive queries (user-created searches), scrutinize spatial information, amend data in maps, and here the fallout of every these operations. Geographic information science is the science basic geographic concept, application, and systems.

The first acknowledged utilize of the expression “Geographic Information System” by Roger Tomlinson in the year 1968 .

Application

GIS is a comparatively wide phrase that is able to pass on to a quantity of poles apart technology, process, and method. It is fond of too many operations and has lots of application interrelated to engineering, scheduling, administration, transfer/logistics, cover, telecommunications, and selling. In favor of that cause, GIS and location astuteness applications can be the groundwork for scores of location-enabled services that rely on inquiry, apparition and spreading of fallout for mutual decision making. GIS provide a mechanically strong podium to all variety of setting stand production personals to update data geographically lacking slaying time to stopover the ground and keep posted in database physically. GIS whilst incorporated with other commanding venture solutions like SAP, help create powerful decision support structure at enterprise echelon.

History of Development

In 1854 John Snow depict a cholera occurrence in London by means of points to characterize the location of some personage cases, maybe the most basic use of a geographic methodology in epidemiology. His cram of the giving out of cholera led to the spring of the disease, a unhygienic water pump (the Broad Street Pump, whose feel he disconnected, thus terminate the outbreak).

FIG: 1.2 E. W. GILBERT’S VERSION (1958) OF JOHN SNOW’S 1855 MAP OF THE SOHOCHOLERA OUTBREAK SHOWING THE CLUSTERS OF CHOLERA CASES IN THE LONDON EPIDEMIC OF 1854

Whilst the indispensable rudiments of topography and matter exist until that time in cartography, the John Snow map was sole, using cartographic methods not only to describe but also to consider clusters of geographically dependent phenomena.

The premature 20th century saw the enlargement of photo zincography, which tolerable maps to be rip into layers, for example one layer for vegetation and another for water. This was predominantly used for print contours ‘ drawing these was a labor-intensive task but have them a detach layer inevitable they could be work on lacking the supplementary layers to baffle the draughtsman. This work was originally wan on glass plates but anon plastic film was introduce, with the recompense of mortal lighter, with less storage space and individual less brittle, among others. While all the layers are completed, they were mutual into one image using a large process camera. Formerly color printing came in; the layers idea was also used for creating split printing plates for each color. While the utilize of layers to a large extent later become one of the foremost typical features of a fashionable GIS, the photographic route just describe is not painstaking to be a GIS in itself ‘ as the maps were immediately images with no database to link them to.

Computer hardware development spur by nuclear weapon investigate led to general-purpose computer “mapping” application by the early 1960s.
The year 1960 saw the expansion of the world’s first true operational GIS in Ottawa, Ontario, Canada by the federal Department of Forestry and Rural Development. Developed by Dr. Roger Tomlinson, it be call the Canada Geographic Information System (CGIS) and was used to accumulate, question, and stage-manage data collected for the Canada Land Inventory ‘ an endeavor to resolve the land potential for rural Canada by mapping information about soils, agriculture, recreation, wildlife, waterfowl, forestry and land use at a scale of 1:50,000. A rating classification factor was also added to permit analysis.

CGIS was an perfection over “computer mapping” applications as it provide capability for overlie, quantity, and digitizing/scanning. It support a national match up system that spanned the continent, coded lines as arcs having a true embedded topology and it store the attribute and location in sequence in take apart files. As a result of this, Tomlinson has grow to be branded as the “father of GIS”, for the most part for his use of overlays in promote the spatial analysis of convergent geographic data.

CGIS lasted into the 1990’s and built a bulky digital land source database in Canada. It was urban as a mainframe-based system in support of federal and provincial resource planning and management. Its potency was continent-wide scrutiny of intricate datasets. The CGIS was not at all presented commercially.

In 1964 Howard T. Fisher formed the Laboratory for Computer Graphics and Spatial Analysis at the Harvard Graduate School of Design (LCGSA 1965’1991), where a numeral of vital theoretical concept in spatial data conduct were developed, and which by the 1970s had disseminated seminal software code and systems, such as SYMAP, GRID, and ODYSSEY ‘ that serve as sources for subsequent commercial development’to universities, research centers and corporations worldwide.

By the premature 1980s, M&S Computing (later Intergraph) beside with Bentley Systems Incorporated for the CAD platform, Environmental Systems Research Institute (ESRI), CARIS (Computer Aided Resource Information System), MapInfo Corporation and ERDAS (Earth Resource Data Analysis System) emerge as commercial vendors of GIS software, productively incorporating many of the CGIS skin, combine the first generation loom to severance of spatial and attribute in sequence with a second generation come up to to organizing attribute data into database structure. In parallel, the enlargement of two public domain systems (MOSS and GRASS GIS) began in the late 1970s and early 1980s.

In 1986, Mapping Display and Analysis System (MIDAS), the first desktop GIS product emerge for the DOS operating system. This was renamed in 1990 to MapInfo for Windows when it was ported to the Microsoft Windows platform. This begins the process of moving GIS from the research department into the business environment.

By the end of the 20th century, the swift expansion in diverse systems had been consolidated and standardized on fairly few platforms and users were beginning to investigate screening GIS data over the Internet, require data arrange and relocate standards. More of late, a mounting number of free, open-source GIS packages run on a collection of operating systems and can be bespoke to act upon definite tasks. Increasingly geospatial data and mapping applications are mortal made available via the World Wide Web.

1.3. ABOUT REMOTE SENSING

The term remote sensing was coined by geographers in the office of naval research of the United States in the 1960s to refer to the acquisition of information about an object without physical contact. The term usually refers to the gathering and processing of information about earth’s environment, particularly its natural and cultural resources, through the use of photographs and related data acquired from an aircraft or a satellite. Today, remote sensing is the preferred method to use if environmental data covering a large area required for a GIS application.
Remote sensing data can be analog or digital in form as well as small or large in scale, according to the type of sensor and platform used for acquiring the data. In some usage, remote sensing refers only to imaginary acquired by sensors using electronic scanning ,which detects radiation outside the normal visible range (0.4-0.7um)of the electromagnetic spectrum, such as microwave, radar, and thermal infrared .The term ‘photograph’ is used to refer to the picture acquired by a conventional camera in the visible region of the electromagnetic spectrum and is analog in form ,while the word ‘image’ or ‘imagery’ refers to non-photographic pictures acquired by electronic detectors operating in the invisible portion of the electromagnetic spectrum and is digital in form. One should, however, note that near infrared radiation between 0.8 ad12um is photographically actinic, which means that it can be recorded on near-infrared films using an ordinary camera.

One notable characteristics of remote sensing is that it is not just a data collection process. Remote sensing also includes data analysis: the methods and processes of extracting meaningful spatial information from the remote sensing data for direct input to the GIS. In digital form, remote sensing data are compatible with the raster-based GIS data model and can be readily integrated with other types of raster GIS data.
The advantage of remote sensing is the bird’s ‘eye view or synoptic view it provides, so that environmental data covering a large area of earth can be captured instantaneously and can then be processed to generate map like products. Another advantage of remote sensing is that it can provide multispectral and multi scale data for the GIS database.
1.3.1 PRINCIPLES OF ELECTROMAGNETIC REMOTE SENSING:
Both photographic and non-photographic remote sensing systems record data of reflection and/or emission of electromagnetic energy from earth’s surface (fig 1).
The major sources of electromagnetic energy are the sun, although earth itself can emit geothermal and man-made energy. Electromagnetic radiation is a form of energy derived from oscillating magnetic and electrostatic fields(fig 2) and is capable of transmission through empty space in a plane harmonic wave pattern at the velocity (c) of light(3*10^8ms^-1).The frequency of oscillation (f) is related to the wavelength(??) by the standard wave equation. C= ??f

Fig-1.3.1:REMOTE SESNING WORKINGA)The sun-source C-d)Reflected radiations D)Radar

Electromagnetic radiation occurs as a continuum of wavelengths and frequencies from short wavelength, high-frequency cosmic waves to long-wavelength, low-frequency radio waves. This is known as the electromagnetic spectrum.
Electromagnetic energy generated from the sun is seriously attenuated by its passage through the atmosphere to earth. The atmosphere contains aerosol particles and gas molecules that scatter or absorb the electromagnetic energy according to its wave length.
Electromagnetic radiation with wavelength shorter than 0.3??m is completely absorbed by the ozone (O3) in the upper atmosphere, whereas water particles in clouds absorb and scatter electromagnetic radiation at wavelength less than about 0.3 cm. There are certain ‘transmission windows’ in the atmosphere through which the electromagnetic energy of certain wave-lengths can be fully transmitted. Such as the 3-5??m and 8-14??m transmission windows for thermal infrared energy.
Once the electromagnetic energy reaches earth, it is further modified through interacting with features on the surface of earth .the energy may be reflected, refracted, transmitted, or absorbed. Energy absorbed by an object will be given out again in the form of emitted energy by the object.
A remote sensing system can detect reflect and emitted energy from earth’s surface. The reflection of the radiation energy depends on the surface roughness and the nature of the material .A very smooth surface such as a lake will give rise to total reflection away from the remote sensor (known as specular, or mirror like, reflection) .
Remote sensing image processing is a mature research area allowing real-life applications with clear benefits for the Society. The main goal of remote sensing is as follows:
1. Monitoring and modeling the processes on the Earth’s surface and their interaction, biological and physical variables.
2. Measuring and estimating geographical, biological and physical variables.
3. Identifying materials on the land cover and analyzing the spectral signatures acquired by satellite or airborne sensors.
1.4 ABOUT THE PROJECT
In the proposed paper, we will see how the GIS is using the remote sensing images for classifying the hyper spectral images and these can be classified by using the hyper spectral image classification where it uses may methods but we used only the maximum likelihood algorithm because it can easily calculates the mean and variance of the image which will calculates by using the reasons of interest (ROI’S).
We can considered it by using reasons of interest (ROI’S) where each area is to be calculate the bands of the area which is then calculates the structural system can be defined and by executing the maximum likelihood classification we can find the area which is closer to that area of bands.
In the proposed state each will include the nearest area by fuzzy classification by adding the fuzzy logic to the maximum likelihood classification can be used to find the spatial, spectral and texture can be calculated by these calculation we can get to the specific area of the image and maximum value bandwidths and so many cases we can get to know by these proposed statement.
OBJECTIVE
In the proposed paper, we will see how the GIS is using the remote sensing images for classifying the hyper spectral images and these can be classified by using the hyper spectral image classification where it uses may methods but we used only the maximum likelihood algorithm because it can easily calculates the mean and variance of the image which will calculates by using the reasons of interest (ROI’S).
We can measured it by using reasons of interest (ROI’S) where each area is to be calculate the bands of the area which is then calculates the structural system can be defined and by executing the maximum likelihood classification we can find the area which is closer to that area of bands.
SCOPE OF THE PROJECT
In the proposed state each will include the nearest area by fuzzy classification by adding the fuzzy logic to the maximum likelihood classification can be used to find the spatial, spectral and texture can be calculated by these calculation we can get to the specific area of the image and maximum value bandwidths and so many cases we can get to know by these proposed statement.

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