In this paper, we present several algorithms developed for restoration of motion blurred images. We begin with a single-image based deblurring approach in the case of linear constant motion. This approach is a wavelet-based method with a novel lp-norm regularization term. Due to the introduction of the wavelet and regularization techniques, the approach is rather robust against noise amplification during deconvolution. Then, we further developed a general multi-image based deblurring framework improved from recent works of [1]. The proposed framework is able to effectively take advantage of information contained in the multiple input images, even when they are blurred in the same direction - a case hard to be dealt with by traditional solutions. The proposed methods are evaluated on both simulated and real data, and the obtained experimental results indicate promising results.