An Overview of Interpolation Algorithms for Image Super-Resolution

image awesome-resolution (SR) is a method used to increase the decision of a photo or enhance the pleasant of more than a few photographs by increasing the pixels in the picture or decreasing the noise. The goal of SR is to growth the visible best of a picture at the same time as preserving the semantic content of the photo. The SR algorithms leverage numerous interpolation algorithms to boom the resolution of the images. Interpolation is a method of estimating or filling inside the lacking information points between two known facts factors. In SR, the interpolation algorithms are used to determine the intensity of the colors and pixels for a higher decision picture. The interpolation techniques utilized in SR encompass bi-cubic interpolation, nearest-neighbor interpolation, bilinear interpolation, Lenclos interpolation, trilinear interpolation, and spline interpolation. Bi-cubic interpolation is a generally used technique in SR. it is the handiest interpolation method for up sampling and has a better performance in comparison to linear and nearest-neighbor algorithms. Bi-cubic interpolation divides an input image into several cubic pieces.