what exactly do k and l represent here and why do we add them to m and n respectively?
motoole2
$k$ and $m$ represent coordinates along the x-axis (horizontal direction). $l$ and $n$ represent coordinates along the y-axis (vertical direction). After sampling different pixel values in the kernel ($g[k,l]$), we multiply them with corresponding pixel values from the source image ($f[m+k,n+l]$). The addition of $k$ and $l$ to $m$ and $n$ is required to implement this correlation filter; that is, the pixel value $h[m,n]$ is a function of pixel values in the neighborhood centered at $f[m,n]$.
what exactly do
kandlrepresent here and why do we add them tomandnrespectively?$k$ and $m$ represent coordinates along the x-axis (horizontal direction). $l$ and $n$ represent coordinates along the y-axis (vertical direction). After sampling different pixel values in the kernel ($g[k,l]$), we multiply them with corresponding pixel values from the source image ($f[m+k,n+l]$). The addition of $k$ and $l$ to $m$ and $n$ is required to implement this correlation filter; that is, the pixel value $h[m,n]$ is a function of pixel values in the neighborhood centered at $f[m,n]$.