Adding Gaussian Noise to Speckle Patterns
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Resource Overview
Implementation of Gaussian noise addition to generated speckle patterns for enhanced complexity and realism
Detailed Documentation
In the original context, we can consider adding Gaussian noise to increase the complexity and realism of speckle patterns. This can be implemented using image processing libraries like OpenCV or MATLAB's Image Processing Toolbox, where Gaussian noise is typically added using functions that generate normally distributed random values with specified mean and variance parameters. The common algorithm involves creating a noise matrix matching the speckle pattern dimensions, scaling it by the desired noise level, and adding it to the original image using pixel-wise arithmetic operations. Key functions to implement this include numpy.random.normal() in Python or randn() in MATLAB for noise generation, followed by image addition operations while ensuring proper data type handling to prevent value overflow.
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