Cubic Spline Algorithm in Image Encoding and Decoding

The cubic spline algorithm delivers superior performance for both image encoding and decoding tasks. However, its computational complexity leads to efficiency degradation in practical implementations. To address this limitation, we have developed a fast algorithm that preserves the original quality characteristics while significantly improving processing efficiency. This optimized approach employs strategic preprocessing of control points and implements efficient matrix solving techniques for spline coefficients, reducing the algorithm's computational footprint. The enhanced method maintains the cubic spline's inherent smoothness and precision properties while accelerating both encoding and decoding workflows, making image processing operations more efficient without compromising output quality. Key implementation aspects include optimized memory allocation for coefficient storage and parallelizable computation segments for modern processor architectures.