【摘要】 冗余字典的信号稀疏分解是一种新的信号表示理论,采用超完备的冗余函数系统代替传统的正交基函数,为信号自适应地稀疏扩展提供了极大的灵活性。该文研究了压缩感知理论下DCT冗余字典和规范正交基(Dirac基)与DCT基组成的冗余字典,提出了一种适应于图像分块的自适应冗余字典方法。结合迭代硬阈值(IHT)重构算法,实验结果表明了提出的自适应冗余字典具有更好的信号恢复效果。更多还原

【Abstract】 Signal sparse decomposition of redundant dictionaries is a new theory for signal representation.The theory can adaptively provide a flexible method for signal sparsity extension via using overcomplete redundant function instead of conventional orthonormal-basis function.Based on DCT redundant dictionary and Dirac dictionary,a novel adaptive redundant dictionary is presented by composed Dirac and DCT base.Combining image partition and iterative hard threshold(IHT) algorithm,experiment results show that the adaptive redundant dictionary has higher signal recovery ratio.更多还原