We present a fast and numerically accurate method for expanding digitized $L \times L$ images representing functions on $[-1,1]^2$ supported on the disk $\{x \in \mathbb{R}^2 : |x|<1\}$ in the harmonics (Dirichlet Laplacian eigenfunctions) on the disk. Our method runs in $\mathcal{O}(L^2 \log L)$ operations. This basis is also known as the Fourier-Bessel basis and it has several computational advantages: it is orthogonal, ordered by frequency, and steerable in the sense that images expanded in the basis can be rotated by applying a diagonal transform to the coefficients. Moreover, we show that convolution with radial functions can also be efficiently computed by applying a diagonal transform to the coefficients.
翻译:我们提出了一个快速和数字精确的扩大数字化 $L\time L$L 图像的方法,该方法代表了 $1,1,1,2$ 的功能,在磁盘上支持 $%x\x\ in\mathbb{R}2 :\\xx ⁇ 1 $$在磁盘上的调和器(Dirichlet Laplaceian egencondictions) 。我们的计算方法以 $mathcal{O} (L2\log L) 运行。这个基础也被称为 Fourier-Bessel 基础, 它有几种计算优势: 它是正方形的, 按频率顺序排列, 并且可以向导, 基础扩展的图像可以通过对系数的对角变换来旋转。 此外, 我们显示, 光函数的演进可以通过对角变法来有效计算。