How does nearest neighbour, bilinear and cubic interpolation work in images?

1. What is nearest Neighbour interpolation in image processing?
2. How does interpolation work in image processing?
3. What is cubic interpolation in image processing?
4. Which interpolation method is best in image processing?

What is nearest Neighbour interpolation in image processing?

Nearest-neighbor interpolation (also known as proximal interpolation or, in some contexts, point sampling) is a simple method of multivariate interpolation in one or more dimensions.

How does interpolation work in image processing?

Interpolation works by using known data to estimate values at unknown points. Image interpolation works in two directions, and tries to achieve a best approximation of a pixel's intensity based on the values at surrounding pixels.

What is cubic interpolation in image processing?

Cubic convolution interpolation is a new technique for resampling discrete data. It has a number of desirable features which make it useful for image processing. The technique can be performed efficiently on a digital computer.

Which interpolation method is best in image processing?

BICUBIC INTERPOLATION

Bicubic produces noticeably sharper images than the previous two methods, and is perhaps the ideal combination of processing time and output quality.