Removing Noise

One-Step Noise Removal

The following methods let you remove noise in one step:

Despeckle method (Document/Medical only)

The Despeckle method is designed specifically for removing specks from 1-bit images, such as FAX transmissions or scanned documents.

The Median method is an effective general function for removing salt-and-pepper noise from any kind of image. You control the strength of the method by specifying the size of the neighborhood (the surrounding pixels used for calculating the median value). This method causes minimal blurring of the image.

The Average method can be used to remove uniform and Gausian noise, but there is more blurring of the image than with the median filter. You control the strength of the method by specifying the size of the neighborhood (the surrounding pixels used for calculating the arithmetic mean).

The GaussianFilter method smoothes or blurs an image by applying a Gaussian filter to each pixel of the bitmap. The amount of blur is determined by the size of the neighborhood used by the method.

Creating Your Own Noise Removal Function

The following methods let you create your own function for noise removal:

BinaryFilter method (Document/Medical only)

MaxFilter method (Document/Medical only)

MinFilter method (Document/Medical only)

The binary filters (for erosion and dilation of black objects) can be used for noise removal. The BinaryFilter method applies directional binary filters. The MaxFilter and MinFilter methods let you control the neighborhood size for erosion or dilation. One noise removal technique with these functions is to create two copies of a bitmap, apply a dilation filter to one of them and an erosion filter to the other, then combine the two using Combine with the CB_OP_AVG (averaging) flag. For more information on combining images, refer to Combining Images.