Notation

Symbol	Meaning
\(f[n,m]\)	Discrete image, \(n\) is the row index (downward), \(m\) is the column index (rightward)
\(g[n,m]\)	Output image
\(h[n,m]\)	Convolution kernel / filter
\(\circ\)	Convolution operation
\(\sigma\)	Gaussian standard deviation or noise standard deviation (depending on context)
\(\mathbf{x} = (x, y)^\top\)	Continuous coordinate point
\(\theta\)	Angle (degrees or radians, stated by context)
\(K\)	Kernel/window size (e.g., \(K\times K\))
\(\kappa\)	Knee threshold of the Huber weight