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DESIGN OF IMAGE PROCESSING FILTER IN MAT LAB

Median Filter:

Insignal processing, it is often desirable to be able to perform some kind

ofnoise reduction on an image or signal. The median filter is a

nonlineardigital filtering technique, often used to removenoise.Such noise

reduction is a typical pre-processing step to improve the results of later

processing (for example, edge detection on an image). Median filtering is

very widely used in digitalimage processing because, under certain

conditions, it preserves edges while removing noise.

The main idea of the median filter is to run through the signal entry by

entry, replacing each entry with themedian of neighbouring entries. The

pattern of neighbours is called the "window", which slides, entry by entry,

over the entire signal. For 1D signals, the most obvious window is just the

first few preceding and following entries, whereas for 2D (or higher-

dimensional) signals such as images, more complex window patterns are

possible (such as "box" or "cross" patterns). Note that if the window has an

odd number of entries, then themedian are simple to define, it is just the

middle value after all the entries in the window are sorted numerically. For

an even number of entries, there is more than one possible median.

http://en.wikipedia.org/wiki/Signal_processinghttp://en.wikipedia.org/wiki/Noise_reductionhttp://en.wikipedia.org/wiki/Digital_filterhttp://en.wikipedia.org/wiki/Signal_noisehttp://en.wikipedia.org/wiki/Edge_detectionhttp://en.wikipedia.org/wiki/Image_processinghttp://en.wikipedia.org/wiki/Medianhttp://en.wikipedia.org/wiki/Medianhttp://en.wikipedia.org/wiki/Medianhttp://en.wikipedia.org/wiki/Medianhttp://en.wikipedia.org/wiki/Image_processinghttp://en.wikipedia.org/wiki/Edge_detectionhttp://en.wikipedia.org/wiki/Signal_noisehttp://en.wikipedia.org/wiki/Digital_filterhttp://en.wikipedia.org/wiki/Noise_reductionhttp://en.wikipedia.org/wiki/Signal_processing

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Unsharp Filter:

Unsharp masking (USM) is animage sharpening technique, often available

indigital image processing software. The "unsharp" of the name derives

from the fact that the technique uses ablurred,or "unsharp", positive image

to create amask of the original image. The unsharped mask is then

combined with the negative image, creating an image that is less blurry

than the original. The resulting image, although clearer, may be a less

accurate representation of the image's subject. In the context ofsignal

processing, an unsharp mask is generally alinear or nonlinear filter that

amplifies the high-frequency components of a signal.

http://en.wikipedia.org/wiki/Image_editinghttp://en.wikipedia.org/wiki/Digital_image_processinghttp://en.wikipedia.org/wiki/Gaussian_blurhttp://en.wikipedia.org/wiki/Mask_(computing)http://en.wikipedia.org/wiki/Signal_processinghttp://en.wikipedia.org/wiki/Signal_processinghttp://en.wikipedia.org/wiki/Linear_filterhttp://en.wikipedia.org/wiki/Nonlinear_filterhttp://en.wikipedia.org/wiki/Nonlinear_filterhttp://en.wikipedia.org/wiki/Linear_filterhttp://en.wikipedia.org/wiki/Signal_processinghttp://en.wikipedia.org/wiki/Signal_processinghttp://en.wikipedia.org/wiki/Mask_(computing)http://en.wikipedia.org/wiki/Gaussian_blurhttp://en.wikipedia.org/wiki/Digital_image_processinghttp://en.wikipedia.org/wiki/Image_editing

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Wiener Filter:

Insignal processing,the Wiener filter is afilter used to produce an estimate

of a desired or target random process by linear time-invariant filtering an

observed noisy process, assuming known stationary signal and noise

spectra, and additive noise. The Wiener filter minimizes the mean square

error between the estimated random process and the desired process.

http://en.wikipedia.org/wiki/Signal_processinghttp://en.wikipedia.org/wiki/Filter_(signal_processing)http://en.wikipedia.org/wiki/Filter_(signal_processing)http://en.wikipedia.org/wiki/Signal_processing

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amount of noise present in a signal by comparison with an estimation of the

desired noiseless signal.