Cross-platform .NET library for digital signal processing

Every journey begins in the mind...

• color spaces and their transformations,
• real and complex algebra,
• statistical distributions,
• special math functions,
• digital response filters,
• discrete orthogonal transforms and more.

• symbolic and graphical visualization of data,
• functional, vector and matrix analysis,
• interpolation, approximation and optimization of functions,
• numerical differentiation and integration,
• solving equations,
• matrix factorization.

• Wavelet Toolbox. Provides wide functionality for the study of discrete and continuous wavelets. The toolbox also includes algorithms for discrete one-dimensional and two-dimensional wavelet transforms of real and complex signals.
• Window Toolbox. Includes a set of tools for synthesizing and orthogonalizing window functions. It implements discrete short-time Fourier and Weyl–Heisenberg transforms (Gabor analysis) for real and complex signals.
• Image Processing Toolbox. Contains efficient algorithms for processing, correcting, and analyzing 32-bit images.
• Video Processing Toolbox. Includes a set of tools for video streaming and processing.

UMapx supports only

• 32 bit types - float, Complex32, etc (compatible with System.Numerics, NAudio and other libraries),
• 32 bit image BitmapData format - Format32bppArgb (compatible with AForge.NET, Accord.NET and so on),
• 24 bit video BitmapData format - Format24bppRgb (32 bit format not recommended).

You can build UMapx from sources or install to your own project using nuget package manager.

using UMapx.Analysis;
using UMapx.Colorspace;
using UMapx.Core;
using UMapx.Decomposition;
using UMapx.Distance;
using UMapx.Distribution;
using UMapx.Imaging;
using UMapx.Response;
using UMapx.Transform;
using UMapx.Video;
using UMapx.Visualization;
using UMapx.Wavelet;
using UMapx.Window;

• Local Laplacian filters - NET Framework desktop application for HDR imaging.
• Portrait mode effect - High quality implementation of the portrait mode effect using Neural Networks.
• FaceONNX - Face analytics library based on deep neural networks and ONNX runtime.

UMapx builds on several existing frameworks (AForge.NET, Accord.NET, ALGLIB, etc.). Some functions have been ported from other programming languages, toolboxes, and libraries (Fortran, MATLAB, C++, Python). The goal of this generalization is to provide a declarative understanding of digital signal processing algorithms and to improve optimization and performance. UMapx is faster than AForge.NET and Accord.NET for common signal-processing tasks and includes a larger set of functions for matrix analysis, linear algebra, and functional analysis.

MIT

A full list of references is given in a separate file.