Signal Processing Stack Exchange
Signal Processing Stack Exchange

Questions tagged [kernel]

A kernel is a function that acts as a parameter that is passed to some algorithm. For example, the two dimensional Gaussian kernel is often used as a parameter for low pass filtering in image processing.

A kernel is a function that acts as a parameter that is passed to some algorithm.

For example, the two dimensional Gaussian kernel is often used as a parameter for low pass filtering in image processing. Sometimes, the kernel in image processing takes the form of a constant matrix, such as the following $5\times 5$ convolution kernel.

enter image description here

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Is there an adjective describing a filter with kernel that has zero mean?

A linear filter with a kernel that has zero mean could be thought of as a "DC-rejecting" filter. Is there a better or more commonly used adjective for such a filter?
Museful
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Why a Convolution Matrix Is Called a Kernel?

According to Wikipedia: In image processing, a kernel, convolution matrix, or mask is a small matrix. I am wondering, why the matrix is called a kernel? Does it has anything to do with kernel concepts in mathematics (e.g., as those mentioned in…
bruin
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Laplacian Operator with and without Diagonal Direction Elements in the Kernel

This is a general question on the laplacian operator, which has two different versions. The first version is : \begin{matrix} 0 & 1 & 0 \\ 1 & -4 & 1 \\ 0 & 1 & 0 \end{matrix} The second version includes the diagonal: \begin{matrix} 1 & 1 &…
kuku
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The Kernel of the Guided Image Filter

I am trying to understand how to calculate kernel matrix for guided image filter. Following is the formula for kernel calculation. where k is window withing pixels i and j belong i assumed that window k is a 3x3 matrix and take following I matrix…
Tab
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Using Convolution as Feature Extraction

I am now studying image processing in my spare time. My understanding of convolution is about 'response to a specific filter': When we have a raw image, or raw signal; and a filter, aka kernel; we apply a 'moving dot product' between the image and…
user152503
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Convolution of Two Kernels [OpenCV]

I've been completely stuck on a portion of my assignment for a few days now. After plenty of searching around, I have been unsuccessful in discovering information that leads me to the correct solution. That said, this is for OpenCV in Python, using…
manapaws
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When should the sum of all elements of a gaussian kernel be zero?

I found an approximation of a 5x5 2D convolution kernel like this : Here, the sum of the elements is zero and this one was used for Laplacian of Gaussian! Another one here : This one has all positive and the sum is not zero and is being used for…
Animesh Pandey
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Applying a 2D Convolution Using 2D FFT

So I was following the article Victor Podlozhnyuk (nVidia) - FFT Based 2D Convolution (Page 7). I have expanded the kernel to the correct way they have done it. However when it comes to the part on clamping to the edge its very confusing. I would…
Simon Balfe
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Is the Laplacian Filter an High Pass Filter (HPF)?

Is this kernel name as mean difference kernel or Laplacian filter? Is mean difference just a method?
Sun
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Applying 2D Image Convolution in Frequency Domain with Replicate Border Conditions in MATLAB

I have created a function that filters an image (250x250) with a gaussian blur kernel (5x5) using FFT and IFFT. I am trying to get my filtered image to equal exactly the filtered image created by the 'imfilter' function using the 'replicate' option.…
Mr guy
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What is the relation between kernel functions, kernels used in convolution and null spaces of a matrix?

I have recently started learning about machine learning and have come across kernels and null spaces. I understand that null space is the set of all vectors that satisfy the equation A.v = 0 (Where A is a matrix). I have been taught that null space…
VaM999
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How to correct phase of Diagonal Volterra kernels obtained with exponential sweep sine?

I'm trying to model a non-linear system using non-linear convolution with Novak's (2010) synchronized exponential sine weep (SESS) that models them with a Generalized Hammerstein (Volterra diagonal). I get pretty clear kernels in terms of SNR but…
OldApprentice
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Volterra Kernel Convolution Method

Here I understand that the first term is a simple convolution of the input signal with first volterra kernel that I have acquired through farina sweep method, my question is if the second term is the convolution of second volterra kernel with our…
skyisfalling
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2D Convolution in the Spatial Domain vs Frequency Domain

Suppose, I have this kernel. -1, -1, -1, -1, 9, -1, -1, -1, -1 Can this kernel be used in a FFT based convolution? How? What could be the reason of my failure? Related: Image Convolution in Frequency Domain. FFT Convolution - 3x3 Kernel
user18425
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Image Processing/ Computer Vision: How is separability of filters implemented?

I am trying to convince myself that a separable 2D filter can be implemented via two 1D filters. So, I took the example of following Sobel filter: $1/8\begin{bmatrix}-1&0&1\\-2&0&2\\-1&0&1\end{bmatrix}$ Based on Szeliski This can be separated as…
skr_robo
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