April 2020
Intermediate to advanced
438 pages
12h 2m
English
Content preview from Python Image Processing Cookbook
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Applying filters to denoise different types of noise in an image
Noise represents random variations of image intensity that cause image quality to deteriorate. Noise can be introduced when the image is captured or transmitted. Image denoising (noise removal) is a vital image processing task that must be done for most of the image processing applications. In this recipe, we will discuss different types of noise with different distributions, such as Gaussian, Salt and Pepper, Speckle, Poisson, and exponential, and image denoising performed for different noise types with a couple of popular filtering techniques (mean and median filters), using the ndimage module from SciPy. The results will be compared for all types of noise.
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