Bilinear interpolation in image processing

Bilinear Interpolation : is a resampling method that uses the distanceweighted average of the four nearest pixel values to estimate a new pixel value. The four cell centers from the input raster are closest to the cell center for the output processing cell will be weighted and based on distance and then averaged.

1. What is bilinear interpolation used for?
2. Which interpolation method is best in image processing?
3. What is the difference between bilinear and bicubic interpolation?

What is bilinear interpolation used for?

In computer vision and image processing, bilinear interpolation is used to resample images and textures. An algorithm is used to map a screen pixel location to a corresponding point on the texture map. A weighted average of the attributes (color, transparency, etc.)

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.

What is the difference between bilinear and bicubic interpolation?

In contrast to bilinear interpolation, which only takes 4 pixels (2×2) into account, bicubic interpolation considers 16 pixels (4×4). Images resampled with bicubic interpolation can have different interpolation artifacts, depending on the b and c values chosen.