Question

Explain Interpolation: Reverse neighbor interpolation, subject is digital image processing

Answer 1

Image interpolation is the process of calculating the unknown pixel values from known pixel values. Interpolation estimate values at unknown points by using known data.For example: if you wanted to know the temperature at noon, but only measured it at 11 AM and 1 PM, you could estimate its value by performing linear interpolation.

Image interpolation occurs when you resize an image from a one-pixel grid to another pixel grid. Image resizing is necessary when you need to increase or decrease the total number of pixels. Zooming refers to an increase in the number of pixels so that when you zoom an image, you will see more detail.

Interpolation estimate values at unknown points by using known data.For example: if you wanted to know the temperature at noon, but only measured it at 11 AM and 1 PM, you could estimate its value by performing linear interpolation.

Interpolation algorithms are classified into two categories;

1. Adaptive

2. Non-adaptive.

Adaptive methods change depending on what they are interpolating whereas non-adaptive algorithms apply fixed patterns to each pixel without considering its other parameter as features, edges of images.

Nearest neighbor interpolation

The nearest neighbor is the most basic and requires the least processing time of all the interpolation algorithms. It only considers one pixel at a time that is the pixel which is the closest one to the interpolated point. This has the effect of simply making each pixel bigger. This can preserve sharp details in pixel art.

Rather than calculating an average value by some weighting criteria or generate an intermediate value based on complicated rules, this type of interpolation method simply determines the “nearest” neighboring pixel and assumes the intensity value of it.