PythonĬout << "Original Height and Width :" << image.rows << "x" << ls << endl As you proceed further, we will discuss resizing with different scale factors and interpolation methods as well. Let’s go through the code example for making an image larger and smaller by resizing with custom height and width.
Image resizing with different Interpolation methods. Resizing an image with a Scaling factor. Image resizing with a custom Width and Height. Reading an Image using OpenCV imread() function. Several methods are available in OpenCV, the choice typically depends on the particular application. Various interpolation techniques come into play to accomplish these operations. This means you need to interpolate new pixels. Increasing the size of an image requires reconstruction of the image. Reducing the size of an image will require resampling of the pixels. width by height), if you want to maintain the same in the resized image too. It is important to keep in mind the original aspect ratio of the image (i.e. To resize an image, scale it along each axis (height and width), considering the specified scale factors or just set the desired height and width. 
Come, let’s learn about image resizing with OpenCV.
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