VC: Convolution-based Image Denoising / Sharpening
We can apply operators to an image. We can make images brighter or darker. We can flip or move the image. Convolution is one specific kind of operator to modify the image or extract features from the image. In this post, I will explain how convolution does denoising and sharpening to images.
Linear Filtering
When you take a picture, you got a blurred picture. How do you solve this blurring? Maybe you can take another shoot or you can use a filter to denoise. As the generation of smartphones begins, people use a lot of applications to filter their pictures. Let’s see how it works.
This is an example of filtering. Some functions determine the output based on the neighboring pixels. This is how a typical filter or kernel works.
One of the simple version of filtering is a linear filter. Cross-correlation and convolution are examples of the linear filter. It replaces each pixel by a linear combination of its neighbors. The above picture shows how it works. They convolve image data and kernel and produce the linear combination. The result is the modified image data.
