【摘要】 针对图像稀疏分解中原子生成速度慢的难题,本文提出了原子生成的一种快速算法。首先根据原子的尺度把原子分成两大类,一类是小原子,一类是大原子。在此基础上,对于小原子,由于其能量集中分布在一个小的范围,所以利用一个小范围生成的局部原子代替整个原子。对于大原子,先生成一个相对应的较小原子,然后通过插值方法生成大原子。实验结果表明,在重建图像的质量没有任何改变的条件下,当图像大小为256×256时,提出的算法使原子生成的速度提高了20多倍。更多还原

【Abstract】 It’s one of main problems in image sparse decomposition that the atom construction process is very time-consuming.To overcome this key problem a new fast algorithm is presented.At first all atoms are divided into two kinds,small atoms and big atoms.For small atoms,the construction of whole atom can be substituted by the construction of a small part of atom because of the concentration of atom energy in a limited region.On the other hand,the construction of big atom can be done by interpolating small atom which is constructed according to the parameters of the big atom except with a smaller scale.Experimental results show that,when the size of the images is 256×256,the proposed algorithm speeds up a little more than 20 times the atom construction process without any loss of the reconstructed image quality compared with the original method.更多还原