MATLAB Implementation of Bilinear Interpolation Method with Code Explanation

Bilinear interpolation is a widely used image processing technique primarily employed for smooth pixel value transitions during image scaling or rotation. Its core principle involves estimating pixel values at new positions by performing two successive linear interpolations (first horizontally, then vertically) using four original pixel values from the 2x2 neighborhood surrounding the target pixel. The implementation approach consists of the following key steps: Coordinate Mapping: Map pixel coordinates from the target image back to the original image coordinate system to find corresponding floating-point positions. Neighborhood Identification: Based on the mapped coordinates, identify the four nearest neighboring pixels (top-left, top-right, bottom-left, bottom-right). Horizontal Interpolation: Perform linear interpolation first on the upper pair and then the lower pair of pixels in the horizontal direction to obtain two intermediate values. Vertical Interpolation: Apply linear interpolation again in the vertical direction using the results from horizontal interpolation to obtain the final pixel value. Boundary Handling: Implement special handling for cases where target coordinates exceed original image boundaries, such as using mirroring or default value padding. In MATLAB implementation, developers can utilize either loop structures or vectorized operations to iterate through all target pixels, with matrix operations significantly optimizing computational efficiency. Weight calculations are based on the relative distances between target coordinates and neighboring pixels - closer pixels receive higher weights. Key MATLAB functions often used include meshgrid for coordinate generation and interp2 for built-in 2D interpolation, though custom implementations provide better understanding of the underlying algorithm. The interpolation weights are typically calculated using the fractional parts of the mapped coordinates, ensuring smooth transitions between pixels.