Simple Image Enhancement Methods
Last lab session, we were tasked to perform point transformation onto images - where one uses a transformation function \(\mathrm{T}[\ ]\) on an image \(f(x,y)\) to obtain another image \(g(x,y)\), or: \begin{equation}g(x,y)=\mathrm{T}\left[f(x,y)\right]\end{equation} [1]. Specifically, we were told to do the following transforms: image negative, logarithmic and gamma transform, contrast stretching and thresholding, and intensity-level slicing. From [1], we see that given that maximum gray value present in the image \(f(x,y)\) is \(L\), then for all gray level values in \(f(x,y)\) is \(r\), the resulting gray values for \(g(x,y)\) is \(s\), and the image's negative is obtained by: \begin{equation}s=L-r \label{nega}\end{equation} whereas for image's logarithmic transform is given by: \begin{equation}s=c\log(1+r) \label{log}\end{equation} and for gamma transform is: \begin{equation}s=cr^\gamma \label{gamma}\end{equation} To stretch the contrast of an image, we stretch c...