This repository provides implementations of two fundamental signal processing filters: the Moving Average Filter and the Median Filter in both C++ and Rust. These filters are essential tools for smoothing data, reducing noise, and extracting meaningful information from datasets.
This project provides robust and efficient implementations of the Moving Average and Median filters in both C++ and Rust. The implementations are designed with performance and safety in mind, leveraging modern programming practices in each language.
- C++ Implementation: Utilizes templates for flexibility, efficient algorithms for median calculation, and adheres to modern C++ best practices.
- Rust Implementation: Emphasizes memory safety without sacrificing performance, leveraging Rust's ownership model and powerful standard library features.
The Moving Average Filter smooths data by replacing each data point with the average of its neighboring points within a specified window. It's widely used for noise reduction in time series data.
Key Features:
- Efficient window sliding using an accumulator.
- Handles boundary conditions by extending the data with the first and last elements.
- Template-based in C++ for type flexibility.
- Safe and performant in Rust with clear error handling.
The Median Filter replaces each data point with the median of its neighboring points within a specified window. It's particularly effective for removing "salt and pepper" noise while preserving edges in signals.
Key Features:
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Utilizes
std::nth_elementin C++ andselect_nth_unstablein Rust for efficient median computation. -
Handles boundary conditions by extending the data with the first and last elements.
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Template-based in C++ for type flexibility.
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Safe and performant in Rust with clear error handling.
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cpp/: Contains the C++ implementation.
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rust/: Contains the Rust implementation.
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LICENSE: Licensing information.
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README.md: Project overview and instructions.
This project is licensed under the MIT License.