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Hands-On Image Processing with Python
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If we remember from the image processing pipeline described in Chapter 1, Getting Started with Image Processing, the immediate next step after image acquisition is image pre-processing. Images are often corrupted by random variations in intensity and illumination or have poor contrast, and therefore can't be used directly and need to be enhanced. This is where the filters are used.
Filtering refers to transforming pixel intensity values toreveal certain image characteristics such as:
The filtered image is described by a discreteconvolution and the filter is described by an x ndiscreteconvolution mask.
This filter allows only high frequencies from the frequency domain representation of the image (obtained with DFT)...