中文摘要：

针对图像处理问题中的模糊性问题，在不确定因素分类与影响分析的基础上实施去模糊处理，并与其他图像的降噪处理作比较．利用仿真实验系统地分析模型与算法的有效性；然后，利用小波变换对图像进行分解，提取小波系数和图像的能量特征，给出匹配与识别方法，通过实验与现有主要的目标识别方法作比较．结果表明，该识别法的识别精度高、速度快，比现有的目标识别方法的识别率平均提高了5．16％．

英文摘要：

This paper studies a variety of fuzzy signal, analyzes the uncertainties classification and their influence, implements to eliminate fuzziness processing, and compares with other methods on image processing with the combining method of simulation and instance experiments, this paper systematically analyzes the validity of the model and algorithms. Moreover, using the wavelet transform to carry out decompose the image, this paper extracts the wavelet coefficient and energy feature, gives the matching and recognition methods, and compares with the existing target recognition methods by experiment. Through experiment results, the proposed recognition method has the high precision, fast speed, which improves an average 5.16 % than that of existing recognition methods. These researches development in this paper can provide an important theoretical reference and practical significance to improve the real-time and accuracy on fuzzy target recognition.