Median Filter Is The Best Solution To Remove Salt and Pepper Noise

.
Q-Median filter is the best solution to remove salt and pepper noise
AnsThe word salt and pepper noise is also speaks out a Impulse noise. The filtering
mainly used for removal of impulse
noise or salt and pepper noise for noise free images and fully recovered by
minimum signal distortion also uncorrupted the
images. For best solutions of removal of salt and pepper noise is a nonlinear
digital filters which is based on order statistics of
median filter. The Median filters are remove noisy signal and unwanted signals
without damaging the corners .Median filter are
operates in low densities but not in higher densities because at higher the image
are blurred and damage the image. The filtering
leaves the uncorrupted pixels and accepts the corrupted pixel. Median filter is
applied to image unconditionally to practiced of
conventional schemes for alert the intensities of remove the noisy signal from
image then the results between the corrupted and
uncorrupted pixels are prior to applying nonlinear filtering is highly desirable
in images.
Q-Image resulting from poor illumination cannot be segmented easily.
The
region
based approach is widely used in color

image segmentation because it considers the color information and spatial details at the same time
edges between two ob jects with the
same brightness but dierent hue can be detected in color images
edges between two ob jects with the
same brightness but dierent hue can be detected in color images
Q-Convolution in the spatial domain is the same as multiplication in the frequency domain
Take a function, f, and compute its Fourier transform, F
Take a filter, g, and compute its Fourier transform, G
Compute H=FG
Take the inverse Fourier transform of H, to get h
Then h=fg
Multiplication in the spatial domain is the same as convolution in the frequency domain
Q-Linear phase filters are always IIR.

Linear phase is a property of a filter, where the phase response of the filter is a linear
function of frequency. The result is that all frequency components of the input signal are
shifted in time (usually delayed) by the same constant amount, which is referred to as
the phase delay. And consequently, there is no phase distortion due to the time delay of
frequencies relative to one another.
For discrete-time signals, perfect linear phase is easily achieved with a finite impulse
response (FIR) filter. Approximations can be achieved with infinite impulse response (IIR)
designs, which are more computationally efficient. Several techniques are:
a Bessel transfer function which has a maximally flat group delay
a maximally flat group delay approximation function
a phase equalizer
Q-Fora causalsystemI h(n) Itendsto zero,as n tendsto infinity,the systemis stable

Stability: An LTI system is "stable" if its impulse response {h[n]} satisfies is finite
This means that {h[n]} must be either a finite impulse response or an impulse response whose
samples decay towards zero as n tends to infinity.
Causality: Any practical LTI system operating in real time must be "causal" which means that its
impulse response {h[n]} must satisfy h[n] = 0 for n < 0. A non-causal system would need a crystal
ball to predict the future.
QFIR filters are always stable?
FIR is always stable and the zeros can be wherever they want including outside the unit circle.
Example: the filter [1 -6 11 -6] has zeros at z = 1, 2 and 3
Q-A stable, causal FIR filter has its poles lying any where inside the unit circle in
the z-plane.
A stable and causal sequence has all its poles inside the unit circle.
The transfer function allows one to judge whether or not a system is bounded-input,
bounded-output (BIBO) stable. To be specific, the BIBO stability criterion requires that
the ROC of the system includes the unit circle. For example, for a causal system, all poles
of the transfer function have to have an absolute value smaller than one. In other words, all
poles must be located within a unit circle in the
The poles are defined as the values of
Clearly, if
-plane.
which make the denominator of
then the poles are not located at the origin of the
equal to 0:
-plane. This is in
contrast to the FIR filter where all poles are located at the origin, and is therefore always
stable.
IIR filters are sometimes preferred over FIR filters because an IIR filter can achieve a
much sharper transition region roll-off than an FIR filter of the same order.

Median Filter Is The Best Solution To Remove Salt and Pepper Noise

Uploaded by

Copyright:

Available Formats

Median Filter Is The Best Solution To Remove Salt and Pepper Noise

Uploaded by

Document Information

Original Title

Copyright

Available Formats

Share this document

Share or Embed Document

Sharing Options

Did you find this document useful?

Is this content inappropriate?

Copyright:

Available Formats

Median Filter Is The Best Solution To Remove Salt and Pepper Noise

Uploaded by

Copyright:

Available Formats

.

Q-Image resulting from poor illumination cannot be segmented easily.

based approach is widely used in color

Take a function, f, and compute its Fourier transform, F

Take a filter, g, and compute its Fourier transform, G

Take the inverse Fourier transform of H, to get h

Q-Linear phase filters are always IIR.

a Bessel transfer function which has a maximally flat group delay

a maximally flat group delay approximation function

Q-Fora causalsystemI h(n) Itendsto zero,as n tendsto infinity,the systemis stable

QFIR filters are always stable?

which make the denominator of

then the poles are not located at the origin of the

You might also like