BCS-SPL将图像的基于块的压缩感测采样（BCS）与平滑的投影Landweber（SPL）迭代重建相结合。采样是通过逐块应用随机矩阵来驱动的，而重建则是预期的Landweber（PL）重建（也称为迭代硬阈值（IHT））的变体，其结合平滑操作（维纳滤波）减少块效应。实质上，除了PL所固有的稀疏性之外，这种滤波操作还能提供平滑性。(BCS-SPL combines block-based compressed-sensing sampling (BCS) of an image with a smoothed projected-Landweber (SPL) iterative reconstruction. Sampling is driven by random matrices applied on a block-by-block basis, while the reconstruction is a variant of projected Landweber (PL) reconstruction (also known as iterative hard thresholding (IHT)) that incorporates a smoothing operation (Wiener filtering) intended to reducing blocking artifacts. In essence, this filtering operation imposes smoothness in addition to the sparsity inherent to PL.)