Linear filters

Linear filters

A linear filter is a type of filter that produces an output signal that is directly proportional to the input signal, with the relationship between the two signals being described by a convolution. Linear filters are commonly used to separate desired signals from interfering noise or other signals, and are one of two main types of filters, the other being non-linear filters.From: Comprehensive Dictionary of Electrical Engineering [2018], Nonlinear Digital Filtering with Python [2019], Image Processing and Acquisition using Python [2020], Phase congruency-based filtering approach combined with a convolutional network for lung CT image analysis [2021]

Spatial Filters

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Published in Ravishankar Chityala, Sridevi Pudipeddi, Image Processing and Acquisition using Python, 2020

Ravishankar Chityala, Sridevi Pudipeddi

There are two types of filters: linear filters and non-linear filters. Linear filters include mean, Laplacian and Laplacian of Gaussian. Non-linear filters include median, maximum, minimum, Sobel, Prewitt and Canny filters.

Phase congruency-based filtering approach combined with a convolutional network for lung CT image analysis

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Published in The Imaging Science Journal, 2021

Mohamed Ben Gharsallah, Hassene Seddik

Image filters can be categorized into three principal classes (Figure 2): spatial, transform domain and hybrid filtering. Spatial filtering uses conventional techniques of image filtering, which works directly on the pixels of images. Though categorized as classical does not mean the filtering methods on spatial domain finishes to be recommended. Principally, this filtering technique may be classified into two classes, linear and non-linear filters. Transform domain filter methods based on low pass frequency filtering have been proposed to reduce the additive noise that taints a digital image. These filtering techniques reduce noise very well in homogeneous areas of the image but also have the major disadvantage of also strongly attenuating the high frequencies of the image as contours, details and texture of the image.

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Spatial Filters

Phase congruency-based filtering approach combined with a convolutional network for lung CT image analysis