Using Mean Filter And Show How The Window Size Of The Filter

Affects Filtering

TASIRA ADNEEN (10.01.05.041)SATYAJIT NAG(10.01.05.042)

FERDAUS ALAM(10.01.05.044)FAHIMUL ISLAM(10.01.05.045)

MD. ABDULLAH ALL MAMUN(10.01.05.047)

OUTLINES

• Definition• Basic Concept about Mean Filter• Algorithm• Function• Code operation overview• Comparisons with other filtering• Final filtered output concepts• Advantages• Disadvantages• Utilizations• Summary

Audio Filter Conception

• Working in the certain audio frequency range.• frequency dependent amplifier• Noise reduction is the process of removing noise

from a signal

Mean Filter for window size of the filter affects

• Mean filter, or average filter is windowed filter of linear class, that smoothes signal .The filter works as low-pass one

• Replaces the center value in the window with the average.

• filter is for any element of the signal take an average across its neighborhood.

Example

• Mean filtering of a single 3x3 window of values• Center value is replaced by the mean of all nine values

Concepts

• Simple Averaging Formulation.sum up elements and divide the sum by the number of elements.

• Filtered 1D signal by mean filter-

Algorithm• Place a window over element• Take an averagePSEUDO CODE FOR MEAN FILTER WITH WINDOW OF SIZE 5 :** Move window through all elements of the signal**for (int i = 2; i < N - 2; ++i)**Take the average_result[i - 2] = (signal[i - 2]+ signal[i - 1]+ signal[i]+signal[i + 1]+signal[i + 2])/ 5) signal input signal result output signal N length of the signalfor i = (N-1): length(yn)-(N-2)

x(i)= (yn(i-(N/2))+yn(i) + yn(i+(N/2)))/Nyn = q' + 1*randn(1,length(q)) adding noise

Edge Treating

• Window filters there is some problem of edge treating.

• signal should be extended.

Functions

• Noise reduction process • read a audio signal before filtering it for noise using

wavread function• record a audio as a wav format in range of 1 min• reading a signal named speech_dft.wan• Sampling• Filtering• Noise adding• Denoising

Sampling

• Sample the signal at different frequencies.• Sampling in high frequencies results a better signal.• Filter function and better algorithm for less use of

memory and time.

Filtering and Denoising Process

• Select the portion of the signal• Determining the range of the signal for filtering• More points need a better filtering function• Adding noise• Filtering with using Filter Function• Technique used for signal denoising

Signal Observations At Different Point of

Operation

Comparison Of Mean Filter With other Audio filters

Comparing with Median Filter Order filters difference. mean filter

smooth out local variations within an audio Signal.

median filter selects the middle value from the original set of recorded signal and mean filters function by finding some form of

an average within window based filtering.

Maximum and minimum filters are two order filters that ,using for elimination noise.

Comparison Of Mean Filter With other Audio filters

• Comparing With Gaussian Filtergeometric mean filter works best with

gaussian noise and retains detail information better .In Gaussian Noise, each signal will be changed

from its original value by a small amounta smoothing mean filter sets each sample of

average value, or a weighted average, of itself and its nearby neighbors. And the Gaussian

filter is just one possible set of weights.Gaussian filter is similar to mean filter. The

difference between them is that in mean filter, every neighbor has the same contribution to the final value.

Comparison Of Mean Filter With other Audio filters

• Comparing With Moving Average filter A moving average filter smoothes data by replacing each data point with the average of the neighboring data points defined within the span which’s quite similar to mean filter functionThe span must be odd, in case of moving average filter and The span can be even or odd in mean filter.

The data point to be smoothed must be at the center of the span

For example, To smooth data using a moving average filter with a span of 5.ys(1) = y(1)

ys(2) = (y(1)+y(2)+y(3))/3

ys(3) = (y(1)+y(2)+y(3)+y(4)+y(5))/5

ys(4) = (y(2)+y(3)+y(4)+y(5)+y(6))/5

Advantages of Mean Filter

• Mean filtering is a non-linear filtering technique which is sometimes useful as it can preserve sharp features in an Audio signal filtering noise.

• The most basic of this filter operation is the arithmetic mean filtering which finds the arithmetic average for corresponding reduction of noise from audio input.

• Fault detection analysis is possible to improve by noise elimination.• Mean filtering is a simple, intuitive and easy to implement method of

smoothing images.

Disadvantages of Mean Filter

• Low frequency information in the background has not been affected significantly by filtering.

• the mean filter would cope with Gaussian noise which was not symmetric about zero.

• It is difficult to treat analytically the effect of a median filter. There is no error propagation.

Utilizations

• Mean filtering is most commonly used as a simple method for reducing in a signal.

• noise filtering provide more accurate detection and localization of defects on distorted image .

• It is used as an edge detector on the image processing.

Final Output Observations• Through this whole process we produced an

audio signal and took a portion of it and added noise with it. Then we did filtering(Mean).Then we saw the final output of this filtering process .We se that this output is with huge amount of noise. That is our system error. We can represent this error by a plotting a curve.

Error curve

• The effect of this filter on an audio signal is that the audio signal is reduced in strength. However, the audio signal still remain clearly audible. But also the `clear' audio signal is affected. With filter lengths greater than 5, the quality of the output audio signal degrades rapidly. This filter behaves like a crude(raw/natural) low pass filter.

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