MATLAB Implementation of Bilinear Interpolation

This MATLAB implementation of bilinear interpolation can be used for motion compensation and reconstruction of processed images.

Bilinear interpolation is an image processing technique that estimates unknown data points by interpolating between known data points. In MATLAB, the bilinear interpolation algorithm can be implemented to achieve image reconstruction and motion compensation. This algorithm effectively enhances image quality and clarity, making processed images more realistic and authentic. The implementation typically involves calculating weighted averages of four surrounding pixels using the formula: f(x,y) = (1-α)(1-β)f(x1,y1) + α(1-β)f(x2,y1) + (1-α)βf(x1,y2) + αβf(x2,y2), where α and β represent the horizontal and vertical fractional distances. By applying bilinear interpolation, blank areas in images can be filled, making the images appear more complete and continuous. The key MATLAB functions involved may include meshgrid for coordinate generation and manual pixel value calculations using matrix operations. This implementation is particularly useful for image processing and reconstruction tasks requiring smooth transitions between pixels.