针对现有多重分形谱对噪声敏感的问题，该文提出了一种基于多重加权法的多重分形谱算法。并首先介绍了基于测度理论的多重分形谱的定义；然后定义了基于多重加权的概率测度，同时对基于多重加权法的多重分形谱性能进行了分析，最后采取与衬底法、方差法进行仿真比较的方法，进行了线性区间、抗噪声性能和收敛速度的比较。比较结果表明，该算法具有保持和加强图像的局部特性以及突出图像的细微处的特点，不仅克服了多重分形谱对噪声敏感的缺点，而且权重因子收敛快。

Multifractal spectrum algorithm based on multi-weight method(MWM) was presented in a accordance with the presnt multifractal spectrum sensitive to the noises. The definition of multifractal spectrum based onmeasurement theorywas introduced. The probability measure based on MWM was defined that can be used to estimate the multifractal spectrum. The capability of multifractal spectrum of MWM was analyzed. In the paper we analyzed the linear region, the anti-noise performance and the convergence of MWM compared to the Bottom interface and variance. The above approach showed that the noise can be reduced effectively and the fine property can be stressed. The local property of an image can remained muchmore and the weighted factor is converged quickly than the approach based on Bottom interface and variance.