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4

Take a look at the literature that does similar things for facial recognition -- search for the term "eigenface", for example. The point to make in this context is that the information you are looking for does not actually require you to consider high-resolution images. You may have $10,000\times 10,000$ pixels, for which any non-trivial ...


2

We construct an operator based on the assumption that the system is a linear space invariant system. The blurred image is denoted $b$ and the input is denoted $x$. Since the convolution is commutative, we can write $ \begin{align} b &= h*x\\ &=x*h \end{align} $ So we can have two equal representations using the matrices $H$ and $X$ corresponding to ...


1

Let us proceed systematically: numerical precision of data (you said from medical imaging) number of operations required for standard methods (as from libraries) possible out-of-core computation (i.e. not the whole matrix at all times in memory). In all cases, I am afraid, you would have to be prepared to suffer. Incidentally, out-of-core methods are very ...


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