1 files changed, 43 insertions, 58 deletions

diff --git a/tools/spectral_editor/dct.js b/tools/spectral_editor/dct.js
index deff8a9..435a7e8 100644
--- a/tools/spectral_editor/dct.js
+++ b/tools/spectral_editor/dct.js
@@ -1,20 +1,10 @@
 const dctSize = 512; // Default DCT size, read from header
 
 // --- Utility Functions for Audio Processing ---
+// Fast O(N log N) IDCT using FFT
 // JavaScript equivalent of C++ idct_512
 function javascript_idct_512(input) {
-    const output = new Float32Array(dctSize);
-    const PI = Math.PI;
-    const N = dctSize;
-
-    for (let n = 0; n < N; ++n) {
-        let sum = input[0] / 2.0;
-        for (let k = 1; k < N; ++k) {
-            sum += input[k] * Math.cos((PI / N) * k * (n + 0.5));
-        }
-        output[n] = sum * (2.0 / N);
-    }
-    return output;
+    return javascript_idct_512_fft(input);
 }
 
 // Hanning window for smooth audio transitions (JavaScript equivalent)
@@ -127,95 +117,90 @@ function fftInverse(real, imag, N) {
     }
 }
 
-// DCT-II via FFT using double-and-mirror method (matches C++ dct_fft)
-// This is a more robust algorithm that avoids reordering issues
+// DCT-II via FFT using reordering method (matches C++ dct_fft)
+// Reference: Numerical Recipes Chapter 12.3
 function javascript_dct_fft(input, N) {
     const PI = Math.PI;
 
-    // Allocate arrays for 2N-point FFT
-    const M = 2 * N;
-    const real = new Float32Array(M);
-    const imag = new Float32Array(M);
+    // Allocate arrays for N-point FFT
+    const real = new Float32Array(N);
+    const imag = new Float32Array(N);
 
-    // Pack input: [x[0], x[1], ..., x[N-1], x[N-1], x[N-2], ..., x[1]]
-    // This creates even symmetry for real-valued DCT
-    for (let i = 0; i < N; i++) {
-        real[i] = input[i];
-    }
-    for (let i = 0; i < N; i++) {
-        real[N + i] = input[N - 1 - i];
+    // Reorder input: even indices first, then odd indices reversed
+    // [x[0], x[2], x[4], ...] followed by [x[N-1], x[N-3], x[N-5], ...]
+    for (let i = 0; i < N / 2; i++) {
+        real[i] = input[2 * i];           // Even indices: 0, 2, 4, ...
+        real[N - 1 - i] = input[2 * i + 1]; // Odd indices reversed: N-1, N-3, ...
     }
     // imag is already zeros (Float32Array default)
 
-    // Apply 2N-point FFT
-    fftForward(real, imag, M);
+    // Apply N-point FFT
+    fftForward(real, imag, N);
 
-    // Extract DCT coefficients
+    // Extract DCT coefficients with phase correction
     // DCT[k] = Re{FFT[k] * exp(-j*pi*k/(2*N))} * normalization
-    // Note: Need to divide by 2 because we doubled the signal length
     const output = new Float32Array(N);
     for (let k = 0; k < N; k++) {
         const angle = -PI * k / (2.0 * N);
         const wr = Math.cos(angle);
         const wi = Math.sin(angle);
 
-        // Complex multiplication: (real + j*imag) * (wr + j*wi)
+        // Complex multiplication: (real[k] + j*imag[k]) * (wr + j*wi)
         // Real part: real*wr - imag*wi
         const dct_value = real[k] * wr - imag[k] * wi;
 
-        // Apply DCT-II normalization (divide by 2 for double-length FFT)
+        // Apply DCT-II normalization
         if (k === 0) {
-            output[k] = dct_value * Math.sqrt(1.0 / N) / 2.0;
+            output[k] = dct_value * Math.sqrt(1.0 / N);
         } else {
-            output[k] = dct_value * Math.sqrt(2.0 / N) / 2.0;
+            output[k] = dct_value * Math.sqrt(2.0 / N);
         }
     }
 
     return output;
 }
 
-// IDCT (Inverse DCT-II) via FFT using double-and-mirror method (matches C++ idct_fft)
+// IDCT (DCT-III) via FFT using reordering method (matches C++ idct_fft)
+// Reference: Numerical Recipes Chapter 12.3
 function javascript_idct_fft(input, N) {
     const PI = Math.PI;
 
-    // Allocate arrays for 2N-point FFT
-    const M = 2 * N;
-    const real = new Float32Array(M);
-    const imag = new Float32Array(M);
+    // Allocate arrays for N-point FFT
+    const real = new Float32Array(N);
+    const imag = new Float32Array(N);
 
-    // Prepare FFT input from DCT coefficients
-    // IDCT = Re{IFFT[DCT * exp(j*pi*k/(2*N))]} * 2
+    // Prepare FFT input with inverse phase correction
+    // FFT[k] = DCT[k] * exp(+j*pi*k/(2*N)) / normalization
+    // Note: DCT-III needs factor of 2 for AC terms
     for (let k = 0; k < N; k++) {
-        const angle = PI * k / (2.0 * N);  // Positive for inverse
+        const angle = PI * k / (2.0 * N);  // Positive angle for inverse
         const wr = Math.cos(angle);
         const wi = Math.sin(angle);
 
-        // Apply inverse normalization
-        let scaled_input;
+        // Inverse of DCT-II normalization with correct DCT-III scaling
+        let scaled;
         if (k === 0) {
-            scaled_input = input[k] * Math.sqrt(N) * 2.0;
+            scaled = input[k] / Math.sqrt(1.0 / N);
         } else {
-            scaled_input = input[k] * Math.sqrt(N / 2.0) * 2.0;
+            // DCT-III needs factor of 2 for AC terms
+            scaled = input[k] / Math.sqrt(2.0 / N) * 2.0;
         }
 
-        // Complex multiplication: DCT[k] * exp(j*theta)
-        real[k] = scaled_input * wr;
-        imag[k] = scaled_input * wi;
-    }
-
-    // Fill second half with conjugate symmetry (for real output)
-    for (let k = 1; k < N; k++) {
-        real[M - k] = real[k];
-        imag[M - k] = -imag[k];
+        // Complex multiplication: scaled * (wr + j*wi)
+        real[k] = scaled * wr;
+        imag[k] = scaled * wi;
     }
 
     // Apply inverse FFT
-    fftInverse(real, imag, M);
+    fftInverse(real, imag, N);
 
-    // Extract first N samples (real part only, imag should be ~0)
+    // Unpack: reverse the reordering from DCT
+    // Even output indices come from first half of FFT output
+    // Odd output indices come from second half (reversed)
     const output = new Float32Array(N);
-    for (let i = 0; i < N; i++) {
-        output[i] = real[i];
+    for (let i = 0; i < N / 2; i++) {
+        output[2 * i] = real[i];              // Even positions
+        output[2 * i + 1] = real[N - 1 - i];  // Odd positions (reversed)
     }
 
     return output;