Recommended Order of Performing Denoising, Deblurring and Super Resolution on an Image

1. What is super resolution in image processing?
2. How does super resolution work deep learning?
3. Why use super resolution?

What is super resolution in image processing?

Super-resolution is based on the idea that a combination of low resolution (noisy) sequence of images of a scene can be used to generate a high resolution image or image sequence. Thus it attempts to reconstruct the original scene image with high resolution given a set of observed images at lower resolution.

How does super resolution work deep learning?

This model uses deep learning to add texture and detail to low resolution satellite imagery and turn it into higher resolution imagery. The model training requires pairs of high and low resolution imagery of the same area.

Why use super resolution?

Photo enlargement made easy.

Super Resolution creates a single image with two times the linear resolution. That means the enhanced image will have twice the width and twice the height of the original image, or four times the total pixel count.