The heatmap function will generate the heatmap image. The function has two parameters: a $3$D matrix representing the RGB image of the

dome area and a $2$D matrix of radiation values. The function returns the heatmap as a $3$D matrix that represents an RGB image.

Review: Working with Images

A $3-$dimensional matrix represents images. The rows and columns correspond to the pixels in the image $($i$.$e$.$ the rows and columns$).$

The third dimension represents the different "channels" of the image $($i$.$e$.$ red$-$green$-$blue or hue$-$saturation$-$value$).$

Because we would like to manipulate the color of the image without changing anything else, the HSV image representation $($see above$)$ is

quite convenient. Before working with the image, you should first convert it to HSV using the rgb$2$hsv function.

Once the image is in HSV format, we can consider each channel separately:

Channel $1$: "Hue". This channel controls which color is used at each pixel, so we want to set its elements according to the

corresponding values in the radiation matrix. To convert from a radiation level to the appropriate hue value, use the formula below:

Channel $2$: "Saturation". This channel controls how strong the color of each pixel is$.$ Set all values in this channel to $1,$ since we want

the colors in the heatmap to be as vibrant as possible.

Channel $3$: "Value". This channel controls how bright are the pixels in the image and thus contains the grayscale picture of the

settlement area. Thus, you should just leave this channel as is$.$

Once you have made the appropriate changes to the HSV image, convert it back to an RGB image with the hsv$2$rgb function before

returning from the heatmap function. Function definition and description

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$,15)$; 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!