Function definition and description imshow$($heatmap$($img$,$ rad$))$;

If your removeNoise function and

functions are working correctly, you should see a picture that looks like this:

This test case is also available in the

file. You can add test cases to this file to continue testing your

function.

You can also quickly test your functions using different radiation scans by typing this into the Command Window:

imshow$($heatmap$($img$,$ removeNoise$($scan$\_$radiation$(100),15)))$;

Which should result in this picture:

This method of testing the functions is exactly the same as the step$-$by$-$step method outlined above, it just puts all of the steps into one

statement. Use whichever method is the most helpful to you!

The function header and comments are provided for you in the file called heatmap$\_$starter.m$.$ Don't forget to remove

from the

filename before you try to call this function.

function $[$ img $]=$ heatmap$($ img, rad $)$

$\%$ Generates a heatmap image by using values

$\%$ from rad to set values in the hue channel for img.

$\%$ Hue values vary smoothly depending on the

$\%$ corresponding radiation level.

$\%$

img: a $3-$dimensional matrix of numbers representing

$\%$ an image in RGB $($red$-$green$-$blue$)$ format, which

$\%$ forms the background to which the heatmap

$\%$ colors are applied.

$\%$ rad: a matrix of numbers representing the radiation

$\%$ measurements, between $0$ and $100$ millisieverts

$\%$ It has the same width and height as the img

$\%$ parameter.

Testing your heatmap function

To test your heatmap function, first read the dome picture into MATLAB by typing this into the Command Window:

img $=$ imread$(\text{'}$dome$\_$area.jpg$\text{'})$;

Then get a set of radiation data:

rad $=sca{n}_r$adiation $(30)$;

Next, call your removeNoise function and save the smoothed data back into rad:

rad $=$ removeNoise$($rad$,15)$;