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Viterbi算法的解码计算的复杂度会随指数增长,在信道状况比较差的条件下解码效果不理想。为了克服这些缺陷,需要尽可能利用已知的信息约束条件和先验知识进行解码,以提高解码效果。本文通过直接加入约束比特的方法将约束维特比方法应用于普通卷积码。与一般的维特比算法相比,在信道状况较差的情况下,该方法通过调整参数可将图像峰值信噪比提高2—10dB左右。实验表明,对于用分层树的集划分算法编码的图像,该方法是一种有效的传输差错控制手段。
The decoding complexity of Viterbi algorithm will increase exponentially, and the decoding performance is not good under the condition of poor channel condition. In order to overcome these defects, we need to use the known information constraints and prior knowledge to decode as much as possible to improve the decoding efficiency. In this paper, constrained Viterbi method is applied to ordinary convolutional codes by directly adding constrained bits. Compared with the conventional Viterbi algorithm, this method can improve the peak signal-to-noise ratio of the image about 2-10dB by adjusting the parameters under poor channel conditions. Experiments show that this method is an effective method to control transmission errors for images coded by hierarchical clustering algorithm.