Adding Various Types of Noise to Images

This program is designed to test other image processing applications by adding various forms of noise to images. The implemented noise types include Gaussian noise, salt-and-pepper noise, additive noise, multiplicative noise, and multiple mixed noise combinations. By utilizing this program during testing phases, developers can better evaluate how other applications perform when handling different noise patterns, thereby improving their robustness and performance. The implementation typically involves using random number generation algorithms: Gaussian noise is created using normally distributed random values added to pixel intensities, while salt-and-pepper noise randomly replaces pixels with maximum or minimum values. Additive noise follows the formula I_noisy = I_original + noise, whereas multiplicative noise uses I_noisy = I_original × noise. The program's flexibility allows users to customize noise parameters such as intensity levels, distribution patterns, and mixing ratios, enabling comprehensive and precise testing scenarios.