February 2014
Intermediate to advanced
390 pages
6h 12m
English
Content preview from Image Processing and Acquisition using PythonBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Chapter 4
Spatial Filters
4.1 Introduction
So far we have covered the basics of Python and its scientific modules. In this chapter, we begin our journey of learning image processing. The first concept we will master is filtering, which is at the heart of image enhancement. Filters are used to remove noise or undesirable impurities. The first derivative and second derivative filters are used to determine edges in an image.
There are two types of filters: linear filters and non-linear filters. Linear filters include mean, Laplacian and Laplacian of Gaussian. Nonlinear filters include median, maximum, minimum, Sobel, Prewitt and Canny filters.
Image enhancement can be accomplished in two domains: spatial and frequency. The spatial domain constitutes ...
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