Reputation: 1239
I am currently doing some seismic modelling and processing in MATLAB, and would like to come up with an easy way of muting parts of various datasets. If I plot the frequency-wavenumber spectrum of some of my data, for instance, I obtain the following result:
Now, say that I want to mute some of the data present here. I could of course attempt to run through the entire matrix represented here and specify a threshold value where everything above said value should be set equal to zero, but this will be very difficult and time-consuming when I later will work with more complicated fk-spectra. I recently learned that MATLAB has an inbuilt function called impoly
which allows me to interactively draw a polygon in plots. So say I, for instance, draw the following polygon in my plot with the impoly
-function:
Is there anything I can do now to set all points within this polygon equal to zero? After defining the polygon as illustrated above I haven't found out how to proceed in order to mute the information contained in the polygon, so if anybody can give me some help here, then i would greatly appreciate it!
Upvotes: 1
Views: 430
Reputation: 104525
Yes, you can use the createMask
function that's part of the impoly
interface once you delineate the polygon in your figure. Once you use create this mask, you can use the mask to index into your data and set the right regions to zero.
Here's a quick example using the pout.tif
image in MATLAB:
im = imread('pout.tif');
figure; imshow(im);
h = impoly;
I get this figure and I draw a polygon inside this image:
Now, use the createMask
function with the handle to the impoly
call to create a binary mask that encapsulates this polygon:
mask = createMask(h);
I get this mask:
imshow(mask);
You can then use this mask to index into your data and set the right regions to 0. First make a copy of the original data then set the data accordingly.
im_zero = im;
im_zero(mask) = 0;
I now get this:
imshow(im_zero);
Note that this only applies to single channel (2D) data. If you want to apply this to multi-channel (3D) data, then perhaps a multiplication channel-wise with the opposite of the mask may be prudent.
Something like this:
im_zero = bsxfun(@times, im, cast(~mask, class(im)));
The above code takes the opposite of the polygon mask, converts it into the same class as the original input im
, then performs an element-wise multiplication of this mask with each channel of the input separately. The result will zero each spatial location that's defined in the mask over all channels.
Upvotes: 4