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Color Image Noise

images sensor process transmission

Definition: In real-world scenarios, noise in color images may result from many sources, such as the underlying physics of the imaging sensor itself, sensor malfunction, flaws in the data transmission procedure, and electronic interference.

Although many sources of sensor noise can be significantly reduced, images are mainly affected by the corruption caused by photon shot noise and dark current shot noise resulting from the photo-electric process. Due to the complex nature of the noise process, the overall acquisition noise is usually modeled as a zero mean white Gaussian noise. Aside from this type of noise, image imperfections resulting from impulsive noise are generated during transmission through a communication channel, with sources ranging from human-made to natural. Thus, noise corruption process in simulated scenarios is usually modeled (Figure 1) using additive Gaussian noise, impulsive noise, or mixed noise.

Real images (Figure 2) are corrupted by real, non-approximated noise which may be different in characteristics and statistical properties depending on application. For example, television images are corrupted by noise caused by atmospheric interference and imperfections of the transmission channel. Noise is introduced into the digitized artworks by scanning damaged and granulated surfaces of the original artworks. The noise floor present in the cDNA microarray image data can be attributed to both source and detector noise introduced due to the nature of microarray technology. In secure imaging applications, the introduction of noise-like information is essential to protect the content of digital visual materials.

Color Image Zooming [next] [back] Color Image Filtering and Enhancement - Fundamentals of Color Imaging, Noise Modeling, Image Filtering Basics

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