|Image Processing Toolbox User's Guide|
Digital images are prone to a variety of types of noise. Noise is the result of errors in the image acquisition process that result in pixel values that do not reflect the true intensities of the real scene. There are several ways that noise can be introduced into an image, depending on how the image is created. For example:
The toolbox provides a number of different ways to remove or reduce noise in an image. Different methods are better for different kinds of noise. The methods available include
To simulate the effects of some of the problems listed above, the toolbox provides the
imnoise function, which you can use to add various types of noise to an image. The examples in this section use this function.
|Decorrelation Stretching||Using Linear Filtering|
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