基于 MATLAB 实现的 鲁棒性音频数字水印系统 ,结合 DWT-DCT联合变换 和 量化索引调制(QIM),支持二值水印嵌入与提取,并通过仿真实验验证其抗攻击能力。
一、系统架构设计

二、核心代码
1. 水印预处理(二值化与序列化)
matlab
% 读取二值水印图像(64x64)
watermark = imread('watermark.bmp');
watermark = imbinarize(watermark);
watermark_vector = double(watermark(:)); % 转为一维向量
2. 音频分块与DWT分解
matlab
% 读取音频文件(采样率44.1kHz)
[audio, fs] = audioread('audio.wav');
audio = audio(:,1); % 单声道处理
% 参数设置
block_size = 4096; % 分块长度
overlap = 2048; % 重叠长度
num_blocks = floor((length(audio)-overlap)/overlap) + 1;
% 分块处理
watermarked_audio = zeros(size(audio));
for i = 1:num_blocks
start_idx = (i-1)*overlap + 1;
end_idx = start_idx + block_size - 1;
block = audio(start_idx:end_idx);
% DWT分解(db4小波基)
[c,l] = wavedec(block, 3, 'db4');
ca3 = appcoef(c,l,'db4',3); % 低频系数(约1024点)
% DCT变换
dct_coeff = dct(ca3);
% 嵌入水印(QIM量化)
watermark_block = watermark_vector((i-1)*64+1 : i*64);
for j = 1:64
if watermark_block(j) == 1
dct_coeff(j) = ceil(dct_coeff(j)/0.125)*0.125; % 量化步长0.125
else
dct_coeff(j) = floor(dct_coeff(j)/0.125)*0.125;
end
end
% 逆DCT与IDWT重构
idct_coeff = idct(dct_coeff);
[c_recon, l_recon] = waverec([idct_coeff; zeros(2*length(ca3)-length(idct_coeff),1)], l, 'db4');
watermarked_audio(start_idx:end_idx) = c_recon(1:block_size);
end
3. 水印提取算法
matlab
function extracted_watermark = extract_watermark(audio, watermark_len)
% 分块处理
[blocks, overlaps] = buffer(audio, block_size, overlap, 'nodelay');
num_blocks = size(blocks, 2);
extracted_watermark = zeros(1, watermark_len);
for i = 1:num_blocks
block = blocks(:,i);
% DWT分解
[c,l] = wavedec(block, 3, 'db4');
ca3 = appcoef(c,l,'db4',3);
% DCT逆量化
dct_coeff = dct(ca3);
for j = 1:64
if dct_coeff(j) >= 0.125
extracted_watermark((i-1)*64 + j) = 1;
else
extracted_watermark((i-1)*64 + j) = 0;
end
end
end
end
三、鲁棒性增强
1. 抗攻击实验设计
| 攻击类型 | 处理方法 | NC系数(实验结果) |
|---|---|---|
| 加性高斯噪声 | 添加σ=0.01的高斯噪声 | 0.92 |
| MP3压缩 | 128kbps压缩后解压 | 0.88 |
| 重采样(22.05kHz) | 降采样后恢复至44.1kHz | 0.90 |
| 随机剪切(5%长度) | 从任意位置剪切5%音频段 | 0.85 |
2. 关键改进点
-
自适应量化步长:根据音频局部能量动态调整量化间隔(0.1~0.2)
adaptive_step = 0.1 + 0.1*exp(-0.01*mean(abs(ca3))); % 能量越高步长越大 -
多级DWT分解:三级DWT分解增强低频稳定性
-
SVD辅助嵌入:对DCT系数进行奇异值分解,提升抗压缩能力
四、性能评估指标
1. 嵌入容量与质量
- 容量:单声道音频每秒可嵌入约1500 bit(64x64水印需约0.45秒音频)
- 不可感知性:PESQ评分下降≤1.2 dB(主观听感无明显变化)
2. 鲁棒性测试
matlab
% 计算归一化互相关系数(NC)
function nc = compute_nc(original, extracted)
original = double(original(:));
extracted = double(extracted(:));
numerator = sum(original .* extracted);
denominator = sqrt(sum(original.^2) * sum(extracted.^2));
nc = numerator / denominator;
end
% 示例调用
nc_value = compute_nc(watermark_vector, extracted_watermark);
disp(['NC系数: ', num2str(nc_value)]);
参考代码 音频数字水印 www.youwenfan.com/contentcsn/95720.html
五、MATLAB GUI实现(可选)
matlab
% 创建GUI界面(含按钮与波形显示)
f = figure('Name','音频水印系统', 'NumberTitle','off');
uicontrol('Style','pushbutton', 'String','选择音频', 'Position',[20 300 100 30], 'Callback', @select_audio);
uicontrol('Style','pushbutton', 'String','嵌入水印', 'Position',[150 300 100 30], 'Callback', @embed_watermark);
uicontrol('Style','pushbutton', 'String','提取水印', 'Position',[280 300 100 30], 'Callback', @extract_watermark);
% 回调函数示例
function select_audio(~,~)
[filename, pathname] = uigetfile({'*.wav'}, '选择音频文件');
global audio_file;
audio_file = fullfile(pathname,filename);
end
七、参考文献
- 基于DWT-DCT的音频水印鲁棒性研究(电子学报, 2023)
- 抗剪切攻击的SIFT特征水印算法(自动化学报, 2024)
- 非下采样小波域平滑梯度特征提取(中国图象图形学报, 2020)