A Novel Bicubic Interpolation-based Image Interpolation Algorithm with Edge Preservation

This document introduces a novel image interpolation algorithm based on bicubic interpolation methodology, which not only demonstrates superior edge preservation capabilities but also enhances image clarity and detail reproduction. The algorithm leverages the fundamental principles of bicubic interpolation, implementing a sophisticated approach to estimate pixel values between known points with higher accuracy, resulting in smoother and more natural-looking interpolated images. Through its implementation of weighted averaging across a 4x4 pixel neighborhood, the algorithm calculates intermediate pixel values using cubic convolution kernels that consider both distance weighting and gradient information. Compared to conventional interpolation methods like bilinear or nearest-neighbor approaches, this advanced algorithm maintains superior image integrity by minimizing edge blurring and artifacts while preserving fine details. The computational implementation typically involves calculating 16 neighboring pixel contributions with carefully designed cubic weighting functions that optimize the trade-off between smoothness and sharpness. This makes the bicubic-based interpolation algorithm particularly valuable for applications requiring high-quality image scaling in digital image processing, computer vision systems, medical imaging, and photographic enhancement where authentic representation of original image characteristics is crucial.