MATLAB Code for Generating Various Noise Types - Poisson, Gaussian, and Impulse Noise

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Resource Overview

Implementation of MATLAB code to generate multiple noise types including Poisson noise for photon counting simulations, Gaussian noise for additive random processes, and impulse noise for sudden signal disturbances, with algorithmic explanations and function descriptions.

Detailed Documentation

This article demonstrates how to implement MATLAB code for generating different types of noise, including Poisson noise, Gaussian noise, and impulse noise. These noise models are essential for simulating real-world scenarios: Poisson noise arises from random discrete events such as photon counting in cameras, Gaussian noise results from the superposition of multiple random processes, while impulse noise represents sudden disturbances caused by transient events. The implementation utilizes key MATLAB functions - poissrnd() for Poisson noise generation requiring λ parameter input, randn() for Gaussian noise with controllable mean and variance, and custom threshold-based algorithms for impulse noise creation. These codes enable accurate simulation of practical data environments, facilitating rigorous testing of algorithm robustness and accuracy through systematic noise injection methodologies.

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