Median Filter

Median filter

• 

Libraries:
DSP System Toolbox / Filtering / Filter Designs
DSP System Toolbox / Statistics

Description

The Median Filter block computes the moving median of the input signal along each channel independently over time. The block uses the sliding window method to compute the moving median. In this method, a window of specified length moves over each channel sample by sample, and the block computes the median of the data in the window. This block performs median filtering on the input data over time. For more details, see Algorithms.

Ports

Input

Port_1 — Data input

column vector | row vector | matrix

Data over which the block computes moving median. The block accepts real-valued or complex-valued multichannel inputs, that is, m-by-n size inputs, where m ≥ 1, and n ≥ 1. The block also accepts variable-size inputs. During simulation, you can change the size of each input channel. However, the number of channels cannot change.

Data Types: single | double
Complex Number Support: Yes

Output

Port_1 — Moving median output

column vector | row vector | matrix

The size of the moving median output matches the size of the input. The block uses the sliding window method to compute the moving median. For more details, see Algorithms.

Data Types: single | double
Complex Number Support: Yes

Parameters

Window length — Length of the sliding window

5 (default) | positive scalar integer

Window length specifies the length of the sliding window in samples.

Simulate using — Type of simulation to run

Interpreted execution (default) | Code generation

Specify the type of simulation to run. You can set this parameter to:

• Interpreted execution –– Simulate model using the MATLAB^® interpreter. This option shortens startup time.

• Code generation –– Simulate model using generated C code. The first time you run a simulation, Simulink^® generates C code for the block. The C code is reused for subsequent simulations as long as the model does not change. This option requires additional startup time but provides faster subsequent simulations.

Block Characteristics

Data Types	double | single
Multidimensional Signals	No
Variable-Size Signals	Yes

Algorithms

Sliding Window Method

In the sliding window method, the output for each input sample is the median of the current sample and the Len - 1 previous samples. Len is the length of the window in samples. To compute the first Len - 1 outputs, when the window does not have enough data yet, the algorithm fills the window with zeros. As an example, to compute the median value when the second input sample comes in, the algorithm fills the window with Len - 2 zeros. The data vector, x, is then the two data samples followed by Len - 2 zeros. This object performs median filtering on the input data over time.

Consider an example of computing the moving median of a streaming input data using the sliding window method. The algorithm uses a window length of 4. With each input sample that comes in, the window of length 4 moves along the data.

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using Simulink® Coder™.

Version History

Introduced in R2016b

R2024a: Change in the default value of Simulate using parameter

The default value of the Simulate using parameter is now Interpreted execution. With this change, the block uses the MATLAB interpreter for simulation by default.