![]() The numpy module will be needed to create the “empty channel”.Īfter that, we will read the original image and split it, like we did before. We will start by importing the cv2 and the numpy modules. For a given channel, create a BGR image that will contain that channel and have the two other empty.Create an “empty” grayscale image that will represent an “empty channel”.Split the original image into three channels.If we want to show each channel as a colored image, we can do the following: But, as seen, each channel corresponded to a two dimensions ndarray that, when shown, was interpreted as a gray scale image. In the previous section we saw how to decompose the image in its three channels and then how to display each channel in a window. Naturally, this rational holds true for the pixels on the other rectangles and the corresponding channels. ![]() In the other channel images, we see black in that area. This is why, in the blue channel image, we see a white rectangle where on the original image was a Blue rectangle. For the Green and Red channel images, this pixel will be equal to 0 and since it is a grayscale image, it corresponds to black. So, if we display the blue channel image in a window, this pixel will be equal to 255 and since it is a grayscale image, it corresponds to white. If we look to a pixel in the blue rectangle of the original colored image, it will have the value of the blue channel equal to 255 and the remaining ones equal to 0: (B=255, G=0, R=0). So, when we decompose each pixel of this area in the three channels, it will have the value 0 in all, which corresponds to black in a grayscale image. Currently, this works with up to 7 or 8 channels (depending on software version an extra one was added recently). To understand the reason, let’s analyze the original image in more detail.įirst we need to consider that the black background pixels have a value equal to 0 for all the channels: (B=0, G=0, R=0). ImageJ has three main modes for displaying multichannel images, accessible from the drop-down menu of the Channels Tool dialog: Composite Merge some or all the channels together for display. Then, for each image of each channel, only the rectangle with the same color is displayed in full white. The first thing that can be noticed is that, as mentioned before, the images are in grayscale. Figure 2 – Output of the program with the 3 channels decomposed.
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