%% 讀取微震圖像（示例為SAC格式）
[data,fs] = readsac('microseismic.sac'); % 讀取時間序列數據
dt = 1/fs; % 採樣間隔
%% 同步壓縮小波變換參數設置
wavelet = 'morl'; % 母小波選擇（morlet/haar/dog）
scales = 1:128; % 尺度範圍
f0 = 1/(4*fs); % 中心頻率參數
%% 執行SS-CWT分解
[C, freq] = cwt(data, scales, wavelet, 'SamplingPeriod', dt, 'VoicesPerOctave', 12);
energy = abs(C).^2; % 時頻能量分佈
%% 時頻區域分割（基於K-means聚類）
[idx, ~] = kmeans(energy(:), 3); % 3類：噪聲/弱信號/強信號
energy_mask = reshape(idx, size(energy));

%% 閾值計算（改進型Stein無偏風險估計）
thr = wthrmngr('dw1ddenoLVL', C, energy_mask);
%% 分區域處理
denoised_C = zeros(size(C));
for i = 1:numel(scales)
for j = 1:size(C,2)
if energy_mask(j,i) == 1 % 噪聲區域
denoised_C(j,i) = wthresh(C(j,i),'h',thr*0.8);
else % 信號區域
denoised_C(j,i) = wthresh(C(j,i),'s',thr*0.5);
end
end
end
%% 逆變換重構
denoised_data = icwt(denoised_C, scales, wavelet, 'SamplingPeriod', dt);

%% 包絡特徵提取
envelope = hilbert(denoised_data);
env_amp = abs(envelope);
%% 改進能量比函數（ER2）
ER2 = movmean(env_amp.^2, [5,5]) ./ movstd(data, [5,5]).^2;
%% 初至時間檢測（AIC準則）
[~, aic_peaks] = findpeaks(-ER2, 'MinPeakHeight', 0.1*max(ER2));
onset_time = aic_peaks(1)/fs; % 首個顯著峯值對應時間

% GPU並行加速
gpu_data = gpuArray(data);
[C_gpu, ~] = cwt(gpu_data, scales, wavelet, 'SamplingPeriod', dt);
% 分塊處理策略
block_size = 1024;
num_blocks = ceil(length(data)/block_size);
denoised_data = zeros(size(data));
parfor i = 1:num_blocks
start_idx = (i-1)*block_size +1;
end_idx = min(i*block_size, length(data));
block = data(start_idx:end_idx);
denoised_block = process_block(block); % 自定義處理函數
denoised_data(start_idx:end_idx) = denoised_block;
end

% 多分辨率融合算法
low_freq = denoise_band(data, 0.1, 10); % 低頻段去噪
mid_freq = denoise_band(data, 10, 100); % 中頻段去噪
high_freq = denoise_band(data, 100, 500); % 高頻段去噪
denoised_data = reconstruct_band(low_freq, mid_freq, high_freq);