![]() The disadvantage of this technique is that image got zoomed but the output is very blurry. You just have to copy the pixels and nothing else. One of the advantage of this zooming technique is, it is very simple. (Original image rows * zooming factor, Original Image cols * zooming factor) Advantage and disadvantage: That means the new image has a dimensions of The next step is to replicate each of the pixel column wise, that we will simply copy the column pixel to its adjacent new column or simply below it.Īs it can be seen from the above example, that an original image of 2 rows and 2 columns has been converted into 4 rows and 4 columns after zooming. When we zoom it row wise, we will just simple copy the rows pixels to its adjacent new cell.Īs you can that in the above matrix, each pixel is replicated twice in the rows. The above image has two rows and two columns, we will first zoom it row wise. If you have an image of 2 rows and 2 columns and you want to zoom it twice or 2 times using pixel replication, here how it can be done.įor a better understanding, the image has been taken in the form of matrix with the pixel values of the image. Each pixel is replicated in this method n times row wise and column wise and you got a zoomed image. ![]() In this method we create new pixels form the already given pixels. This algorithm works on the same principle. As we have already discussed in the tutorial of Sampling, that zooming is nothing but increase amount of sample or pixels. As its name suggest, in this method, we just replicate the neighboring pixels. It is also known as Nearest neighbor interpolation. Method 1: Pixel replication: Introduction: We will start by discussing pixel replication. Pixel replication or (Nearest neighbor interpolation)Įach of the methods have their own advantages and disadvantages. ![]() In this tutorial we are going to formally introduce three methods of zooming that were introduced in the tutorial of Introduction to zooming. ![]()
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