Wavefront raycasting using larger filter kernels for on-the-fly GPU gradient reconstruction

The quality of images generated by volume rendering strongly depends on the accuracy of gradient estimation. However, the most commonly used techniques for on-the-fly gradient reconstruction are still very simple, such as central differences; they generally gather only limited neighbourhood information and thus ultimately produce rather poor quality images. While there are many higher-order reconstruction methods, such as 3×3×3 or 5×5×5 filters, which can improve the quality, their excessive sampling costs have meant that they are generally used only for pre-computed gradients, which are then quantized and stored for later runtime re-interpolation. This may introduce further errors and, significantly, may consume valuable texture memory.