短时傅里叶变换STFT一维数据转换二维图像的方法（Matlab代码和数据）

clear clc close all % load an audio file [x, fs] = audioread('track.wav'); % load an audio file x = x(:, 1); % get the first channel output_folder = './figures'; % 指定输出频谱文件夹路径(此处默认为本代码文件夹) %% 滑动窗口划分样本 window_length = 106150; % 窗口长度 step_size = 106150; % 步长 t = (0:window_length-1)/fs; f=(fs/2)/(window_length/2):(fs/2)/(window_length/2):(fs/2); num_samples = floor((length(x) - window_length) / step_size) + 1; % 样本数量 % 初始化样本矩阵 samples = zeros(window_length, num_samples); % 滑动窗口划分数据样本 for i = 1:num_samples start_index = (i - 1) * step_size + 1; % 窗口起始索引 end_index = start_index + window_length - 1; % 窗口结束索引 % 判断是否滑动至最后一个窗口 if end_index <= length(x) samples(:, i) = x(start_index:end_index); else % 忽略最后一个窗口 break; end end % 显示样本矩阵的大小 fprintf('样本矩阵的大小：[%d, %d]\n', size(samples)); %% 对划分的每个样本进行频谱图计算,并将图像保存在指定文件夹下 [m,n] = size(samples); % define analysis parameters wlen = 1024; % window length (recomended to be power of 2) hop = wlen/4; % hop size (recomended to be power of 2) nfft = 4096; % number of fft points (recomended to be power of 2) % perform STFT win = blackman(wlen, 'periodic'); for g = 1:n %生成RP % 转换为相空间，第一个元素为高度，第二个元素为下一个位置的高度。 X = samples(:,g); [S, f, t] = stft(X, win, hop, nfft, fs); % calculate the coherent amplification of the window C = sum(win)/wlen; % take the amplitude of fft(x) and scale it, so not to be a % function of the length of the window and its coherent amplification S = abs(S)/wlen/C; % correction of the DC & Nyquist component if rem(nfft, 2) % odd nfft excludes Nyquist point S(2:end, :) = S(2:end, :).*2; else % even nfft includes Nyquist point S(2:end-1, :) = S(2:end-1, :).*2; end % convert amplitude spectrum to dB (min = -120 dB) S = 20*log10(S + 1e-6); figure; imagesc(t,f,abs(S)) set(gca,'ydir','normal'); colorbar; title('STFT'); % 构建输出文件名 file_name = sprintf('sample_%d.png', g); % 拼接输出文件路径 output_path = fullfile(output_folder, file_name); % 保存图像 saveas(gcf, output_path); % 关闭当前图像窗口 close(gcf); end