Tech beauty|Entertain with blog: M.tech cse

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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">Restoration improves
image by removing blurring mostly. As image enhancement is subjective process
but image restoration is an objective process. </span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">Restoration attempts to
recover an image that has been degraded by using a prior knowledge of the
degradation phenomenon. Techniques are oriented toward modeling the degradation
and applying the inverse process in order to recover the original image.</span><br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgFVpfhs5m0GGa3smIqlzdv8BW2lVMG5pTHYr2fvnpARKubNkOmDWpQeI1Ixvh8LbL8CmXMmQOXArLJSHodIy-PgJ1PMG3Pgr8fx72Kywq2Z6Okr2chvhlLGpbdamdC4VeUhW8idJNjFGrb/s1600/Untitled.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="236" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgFVpfhs5m0GGa3smIqlzdv8BW2lVMG5pTHYr2fvnpARKubNkOmDWpQeI1Ixvh8LbL8CmXMmQOXArLJSHodIy-PgJ1PMG3Pgr8fx72Kywq2Z6Okr2chvhlLGpbdamdC4VeUhW8idJNjFGrb/s640/Untitled.png" width="640" /></a></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">It refer to remove or
reduce the degradation that have occurred while the digital image was being
obtained.</span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">Degradation may be
occur due to</span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">1. Sensor noise</span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">2. Blur due to camera
miss focus</span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">3. Relative
object-camera motion</span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">4. Random atmospheric
disturbance</span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">5. Others</span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">Example :-Contrast
stretching is considered an enhancement technique but removal of image blur by
applying a deblurring function is considered a restoration technique.</span></div>
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<b style="mso-bidi-font-weight: normal;"><span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">MODEL
OF THE IMAGE DEGRADATION/RESTORATION PROCESS</span></b></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;"> <img alt="" height="153" 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" width="640" /></span></div>
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</span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">Degradation process
operates on a degradation function that operates on an input image with an
additive noise term.</span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">Additive noise term
operates on input image f(x,y) to produce a degraded image g(x,y).Given g(x,y)
some knowledge edge about the degradation function H, and some knowledge about
the additive noise term </span><b>ƞ(x,y) ,</b><span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">the objective of restoration is to obtain an estimate f’(x,y) of the
original image. We want the estimate to be as close as possible to the original
input image and , in general the more we know about H and </span><b>ƞ ,</b><span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">the closer f’(x,y) will be to f(x,y).</span></div>
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</span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">If H is a linear , Positive-invariant process then the degraded image is
given in the special domain by</span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;"><span style="mso-tab-count: 3;">                             </span>g(x,y)
= h(x,y) * f(x,y) + ƞ(x,y)</span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">where h(x,y) is the special representation of the degradation function
and * symbol indicates convolution.</span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">Frequency domain representation</span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">G(u,v) = H(u,v)F(u,v) + N(u,v)</span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">Where the terms in capital letters are Fourier transformation of
corresponding above equation.</span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">These two equations are the basis for most of the restoration material.</span></div>
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<b><span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">Noise Models</span></b></div>
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<b><span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">

</span></b><span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;"></span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">Sources of noise in digital images arise during image acquisition and
transmission. Performance of imaging sensors are affecting by a variety of
factors such as environment conditions during image acquisition and quality of
sensing elements itself. For instance acquiring images with a CCD camera, light
levels and sensor temperature are major factors affecting the amount of noise
in the resulting image.</span></div>
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<br /></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">Spacial characteristics
of noise and whether the noise is correlated with the image frequency
properties refer to the frequency content of noise in the fourier sense.For
example when fourier spectrum of noise is constant , the noise usually is
called white noise.</span></div>
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</span></div>
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<b style="mso-bidi-font-weight: normal;"><span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">NOISE
PROBAILITY DENSITY FUNCTIONS (Refer to Gonzalez book for formulas and graph)</span></b></div>
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<b style="mso-bidi-font-weight: normal;"><span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">Gaussian
noise</span></b></div>
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<br /></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">Because of its
mathematical tractability in both special and frequency domains Gaussian also
called normal noise models are frequently in practice.</span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">This tractability is so
convenient that its often results in Gaussian models being used in situation in
which they are marginally applicable .</span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;"> </span></div>
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<span style="clear: right; color: black; float: right; font-family: "times new roman" , "serif"; font-size: 14pt; line-height: 100%; margin-bottom: 1em; margin-left: 1em;"><img alt="" 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" />
</span></div>
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<span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt;">The PDF of Gaussian random variable, z is given by </span></div>
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<span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt;">z= gray level </span></div>
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<b><span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt;"> </span></b><span style="height: 171px; left: 328px; margin-left: 0px; margin-top: 182px; position: absolute; top: 1882px; width: 198px; z-index: 251662334;"></span><span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 100%;">µ= mean of
average value of z <b>σ</b>= standard deviation</span></div>
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<b></b><br />
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;"></span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">

</span></div>
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">

</span></div>
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<b><u><span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt;">Rayleigh Noise </span></u></b><b><span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt;"></span></b></div>
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<br /></div>
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<span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 109%;">Unlike Gaussian distribution, the Rayleigh distribution
is no symmetric. It is given by the formula. </span></div>
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" 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" /></a><span style="font-family: "times new roman" , "serif"; font-size: 12.0pt;"> </span></div>
<div class="MsoNormal" style="line-height: 10.0pt; margin-bottom: .0001pt; margin-bottom: 0in; mso-layout-grid-align: none; mso-line-height-rule: exactly; mso-pagination: none; text-autospace: none;">
<span style="font-family: "times new roman" , "serif"; font-size: 12.0pt;"> </span><span style="font-family: "times new roman" , "serif"; font-size: 12.0pt;"></span><span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt;">The mean variance of this
density</span></div>
<div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0in; margin-left: 49.35pt; margin-right: 0in; margin-top: 0in; mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;">
<br /></div>
<div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0in; margin-left: 49.35pt; margin-right: 0in; margin-top: 0in; mso-layout-grid-align: none; mso-pagination: none; text-autospace: none;">
<span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt;"> </span><span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">It
is displaced from the origin and skewed   towards the right</span></div>
<br />
<div class="MsoNormal" style="text-align: justify;">
<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;"></span></div>
<div class="MsoNormal" style="text-align: justify;">
<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;"></span></div>
<br />
<br />
<div class="separator" style="clear: both; text-align: left;">
<span style="clear: right; float: right; font-family: "times new roman" , "serif"; font-size: 14pt; line-height: 107%; margin-bottom: 1em; margin-left: 1em;"><span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;"></span></span><span style="clear: right; float: right; font-family: "times new roman" , "serif"; font-size: 14pt; line-height: 107%; margin-bottom: 1em; margin-left: 1em;"><span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;"></span></span></div>
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<b><span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt;"><span style="mso-list: Ignore;">III.<span style="font: 7.0pt "Times New Roman";">        
</span></span></span></b><b><u><span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt;">Erlang (gamma) Noise </span></u></b><b><span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt;"></span></b></div>
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<span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">The PDF of Erlang noise is given by </span><br />
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" 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<span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt;">The mean and variance of this noise is </span></div>
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" 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" /></a> </div>
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<span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt;">Its shape is
similar to Rayleigh disruption.</span><span style="font-family: "times new roman" , "serif"; font-size: 14.0pt;"></span></div>
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<span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;">This equation is referred to as gamma density it is
correct only when the denominator is the gamma function</span><br />
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<span style="font-family: "times new roman" , "serif"; font-size: 14.0pt;"><span style="mso-tab-count: 1;">         </span><b><u><span style="color: black;">Exponential Noise</span></u></b></span></div>
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<span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt;">Exponential
distribution has an exponential shape.</span><span style="font-family: "times new roman" , "serif"; font-size: 14.0pt;"></span></div>
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<span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt;">The PDF of
exponential noise is given as</span><span style="font-family: "times new roman" , "serif"; font-size: 14.0pt;"></span></div>
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<span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt;">Where a>0</span><span style="font-family: "times new roman" , "serif"; font-size: 14.0pt;"></span></div>
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<span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt;">It is a special
case of Erlang with b=1</span><span style="font-family: "times new roman" , "serif"; font-size: 14.0pt;"></span></div>
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<span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt; line-height: 107%;"><img alt="" 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" />                        </span></div>
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<div class="MsoNormal" style="line-height: normal; margin-bottom: .0001pt; margin-bottom: 0in; margin-left: 34.0pt; margin-right: 0in; margin-top: 0in; mso-layout-grid-align: none; mso-list: l0 level1 lfo1; mso-pagination: none; punctuation-wrap: simple; tab-stops: list 34.0pt; text-align: justify; text-autospace: none; text-indent: -28.3pt;">
<b><span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt;"><span style="mso-list: Ignore;">V.<span style="font: 7.0pt "Times New Roman";">         
</span></span></span></b><b><u><span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt;">Uniform Noise </span></u></b><b><span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt;"></span></b></div>
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<span style="color: black; font-family: "times new roman" , "serif"; font-size: 14.0pt;">The PDF of
uniform noise is given by</span></div>
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IMAGE RESTORATION(For expression under given terms refer book Gonzalez)

Restoration improves image by removing blurring mostly. As image enhancement is subjective process but image restoration is an objectiv...