2D FIR Filter & Finite Decomposition

In summary, the conversation discussed a process known as state-dependent filtering, which involves using multiple FIR filters with different states for image processing. This process is also related to polyphase FIR filtering and can be found in various online resources.
  • #1
rivulatus
1
0
Hi All,

I would like to know how can I call or express the following process!

I use a (3x3) 2D FIR Filter for imaging processing with DC = 0, like this:

0 1 1
2 O 2 /8
1 1 0

My filter is such that I can decompose it into finite sates, as my image (medical)
can take 9 finite state (from 0 to 8 ). So instead of having 1 linear FIR filter for
all the states, I have a "FIR" filter for each state. I decompose my filter like that,
where H? is the state

H1 = 0 0 0
0 0 1
0 0 0

H2 = 0 0 0
1 0 1
0 0 0

H3 = 0 0 0
1 0 1
0 1 0

H4 = 0 1 0
1 0 1
0 1 0

H5 = 0 1 1
1 0 1
0 1 0

H6 = 0 1 1
1 0 1
1 1 0

H7 = 0 1 1
2 0 1
1 1 0

H8 = 0 1 1
2 0 2
1 1 0

Obviously, there is no filter for H0, and I notice that it result in a smoother filtration.

I would like to know if there is a term to describe this process?
How can I call it? (is it related to polyphase FIR?)

Where can I find documentation regarding such a process?

Thanks a lot for your help
 
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  • #2
.The process you are describing is known as state-dependent filtering. It is a form of polyphase FIR filtering, where each filter has multiple states depending on the input. State-dependent filtering is used in various applications such as image processing and signal processing. You can find more information about state-dependent filtering in various online resources, including the following: https://www.researchgate.net/public...2https://ieeexplore.ieee.org/document/8767514
 

1. What is a 2D FIR filter?

A 2D Finite Impulse Response (FIR) filter is a type of digital filter used to process 2-dimensional signals, such as images. It is a discrete-time filter that operates on a finite number of input samples and produces a finite number of output samples. The filter is characterized by its impulse response, which is a finite sequence of numbers that determine its behavior.

2. How does a 2D FIR filter work?

A 2D FIR filter works by convolving the input signal with the filter's impulse response. This means that the filter multiplies each input sample by a specific coefficient and sums the results to produce an output sample. The coefficients in the impulse response determine the frequency response of the filter, which allows it to selectively filter certain frequencies in the input signal.

3. What is finite decomposition in the context of 2D FIR filters?

Finite decomposition is a method used to decompose a 2D FIR filter into a series of 1D filters. This method is used to simplify the implementation and speed up the processing of 2D filters. It involves separating the filter into two sequential stages, where the first stage is a 1D filter applied in the horizontal direction and the second stage is a 1D filter applied in the vertical direction.

4. What are the advantages of using finite decomposition for 2D FIR filters?

Finite decomposition offers several advantages for 2D FIR filters. Firstly, it simplifies the implementation of the filter by breaking it down into smaller and simpler 1D filters. This reduces the number of arithmetic operations needed and speeds up the processing. Additionally, finite decomposition allows for efficient hardware implementation and reduces memory requirements, making it suitable for real-time applications.

5. What are some common applications of 2D FIR filters?

2D FIR filters have a wide range of applications, particularly in image and signal processing. They are commonly used for noise reduction, image enhancement, edge detection, and image reconstruction. They are also used in areas such as medical imaging, video compression, and radar signal processing. Additionally, 2D FIR filters are used in various digital communication systems to improve the quality and reliability of transmitted signals.

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