# High Dynamic Range Images

2020-02-26

Today’s exercise is focused on implementation of high dynamic range (HDR) images.

We need a sequence of images:

$I_1 \dots I_n \, ,$ where $$n$$ is number of images.

For each pixel at coordinate $$(i, j)$$ and image $$k$$, we compute a weight:

$w_k(i, j) = \exp\Bigg(- \frac{(I_k(i, j) - 255 \mu)^2}{2 (255 \sigma)^2} \Bigg) \, ,$ where $$\mu = 0.5$$, and $$\sigma = 0.2$$ (you can elaborate on these constants). Weights have to be normalized to the sum of values for every pixel (sum of $$w_k = 1$$).

The final radiance in each pixel can be computed as a sum of weighted pixel colors over set of images:

$R(i, j) = \sum_{k=1}^n w_k(i, j) I_k(i, j) \, .$

Images can be processed in grayscale

or in all three color channels.