# Name

filt_btwl - Butterworth low-pass Fourier filter

# Usage

output = filt_btwl(image, freql, freqh, pad)

## Input

- image
- input image (can be either real or Fourier)
- freql
- low - pass-band frequency
- freqh
- high - stop-band frequency
- pad
- logical flag specifying whether before filtering the image should be padded with zeroes in real space to twice the size (this helps avoiding aliasing artifacts). (Default pad = False).

All frequencies are in absolute frequency units

``f_a``and their valid range is [0:0.5].

## Output

- output
- filtered image. Output image is real when input image is real or Fourier when input image is Fourier

# Method

Fourier transform of the input image is multiplied by a radially symmetric Butterworth filter:

``B(f) = 1.0/sqrt(1.0+(f/(RAD))^(ORDER))``

Value of ORDER determines the filter falloff and RAD corresponds to the cut-off frequency. RAD and ORDER are calculated from the parameters specified by the user using following equations:

``ORDER = [2*log((eps)/sqrt(a^2-1))]/[log((low)/(high))]````RAD = (low)/((eps)^(2/(ORDER)))``

where low and high are the pass-band and stop-band frequencies, respectively, and parameters * eps* and

*are set to 0.882 and 10.624, respectively. Note values of the filter B(f) deviate from 1.0 at frequency low by about 0.2 and from 0.0 at frequency high by about 0.09 (for a low-pass filter.)*

**a**

# Reference

Gonzalez, R. F., Woods, R. E., 2002. Digital Image Processing. Prentice Hall, Upper Saddle River, NJ.

# Author / Maintainer

Pawel A. Penczek

# Keywords

- category 1
- FILTER
- category 2
- FOURIER

# Files

filter.py

# Maturity

- stable
- works for most people, has been tested; test cases/examples available.

# Bugs

None. It is perfect.