DIGITAL_FILTER Function

Standard Library function that constructs finite impulse response digital filters for signal processing.


Desired Effect	Value
No filtering	flow = 0, fhigh = 1
Lowpass filter	flow = 0, 0 fhigh 1
Highpass filter	0 flow 1, fhigh = 1
Bandpass filter	0 flow fhigh 1
Bandstop filter	0 fhigh flow 1

These non-recursive filters require evenly spaced data points. Frequencies are expressed in terms of the Nyquist frequency, 1/2T, where T is the time elapsed between data samples.

The Gibbs Phenomenon variations are oscillations which result from the abrupt truncation of the infinite FFT series. Setting the gibbs parameter either too high or too low may yield unacceptable results.

TIP: A value of 50 for gibbs is a good choice for most filters.

Sample Usage

DIGITAL_FILTER is used extensively in image and signal processing applications to build image or signal filters. It provides a convenient way of creating convolution kernels (containing the filter coefficients)

all you need do is specify the desired filter with respect to the high and low cutoff frequencies, the Gibb's variations, and the number of terms. You can then use the constructed kernels with the CONVOL function to perform the actual filtering operation upon a signal or image.

To evaluate the coefficients of a digital filter and then apply them to a signal, use the following sequence of equations:

Coeff = DIGITAL_FILTER(flow, fhigh, gibbs, nterm)

Filtered_Signal = CONVOL(input_signal, coeff)

The end result is an image or signal that has certain frequencies or bands of frequencies filtered out of it. For example, an electrical engineer may want to filter out high frequency harmonics or low frequency flutter from a signal. This can easily be achieved by using the high and low pass filters constructed with DIGITAL_FILTER as the coefficients in the CONVOL function.

NOTE: Two or more filters created by DIGITAL_FILTER can be combined by addition, subtraction, or averaging to create multiple filtering effects with one filter.

Example 1

A digital signal processing example follows:

av_temp = FLTARR(140)
OPENR, unit, !Data_dir + 'example_air_q.dat', /Get_lun
READF, unit, av_temp, Format='(5X,F9.4)'

; Read the average temperature field from the air quality test dataset.

FREE_LUN, unit
PLOT, av_temp

; Display the original data.

filter = DIGITAL_FILTER(0.0, 0.1, 50, 10)

; Create the convolution kernel for a lowpass filter.

filt_temp = CONVOL(av_temp, filter)

; Filter the data by convolving it with the kernel.

OPLOT, filt_temp, Linestyle=2

; Display the filtered data using a dashed line.

Example 2

An image processing example follows:

mandril = BYTARR(512,512)
OPENR, unit, !Data_dir + 'mandril.img', /Get_lun
READU, unit, mandril

; Read the mandril demo image.

FREE_LUN, unit
WINDOW, XSize=512, YSize=512
TV, mandril

; Display the original image.

mandril = FLOAT(mandril)

; Convert the byte data to floating-point for filtering.

filter = DIGITAL_FILTER(0.0, 0.1, 50, 10)

; Create the convolution kernel for a lowpass filter.

filt_image = CONVOL(mandril, filter)

; Filter the image by convolving it with the kernel.

TV, filt_image

; Display the filtered image.

DIGITAL_FILTER Function

Usage

Input Parameters

Returned Value

Keywords

Discussion

Sample Usage

Example 1

Example 2

See Also