  In this work, we propose a new approach for efficient edge-preserving image
deconvolution. Our algorithm is based on a novel type of explicit image filter
- guided filter. The guided filter can be used as an edge-preserving smoothing
operator like the popular bilateral filter, but has better behaviors near
edges. We propose an efficient iterative algorithm with the decouple of
deblurring and denoising steps in the restoration process. In deblurring step,
we proposed two cost function which could be computed with fast Fourier
transform efficiently. The solution of the first one is used as the guidance
image, and another solution will be filtered in next step. In the denoising
step, the guided filter is used with the two obtained images for efficient
edge-preserving filtering. Furthermore, we derive a simple and effective method
to automatically adjust the regularization parameter at each iteration. We
compare our deconvolution algorithm with many competitive deconvolution
techniques in terms of ISNR and visual quality.
