Enhanced Fast Bilateral Filter Algorithm

The improved fast bilateral filter algorithm implements a three-phase processing approach for efficient image enhancement. The algorithm begins with downsampling the input image to reduce computational complexity and processing time. In the code implementation, this typically involves using interpolation functions like `imresize` in MATLAB or OpenCV's `resize` function with appropriate scaling factors. Following downsampling, the bilateral filter is applied to smooth the image while preserving edges, utilizing both spatial and range Gaussian kernels where parameters like sigma_space and sigma_color control the smoothing intensity. The core filtering operation can be implemented using optimized functions such as OpenCV's `bilateralFilter` or custom implementations leveraging separable kernel approximations for faster computation. Finally, upsampling is performed to restore the image to its original resolution, often using interpolation methods like bicubic or Lanczos to maintain detail fidelity. This enhanced approach significantly improves processing efficiency while maintaining high-quality output, making it suitable for real-time image enhancement applications where both speed and quality are critical requirements.