fix coverity 1134134 1134135 (div by 0)

[kdenlive] / src / lib / audio / fftCorrelation.cpp

diff --git a/src/lib/audio/fftCorrelation.cpp b/src/lib/audio/fftCorrelation.cpp
index fa31409665ecb7e28ecd6f209ce710fa66c85c8a..139ea203d0daaac1c3a62b3949e5628222cf223b 100644 (file)
--- a/src/lib/audio/fftCorrelation.cpp
+++ b/src/lib/audio/fftCorrelation.cpp
@@ -1,4 +1,4 @@
-/*
+ /*
 Copyright (C) 2012  Simon A. Eugster (Granjow)  <simon.eu@gmail.com>
 This file is part of kdenlive. See www.kdenlive.org.
 
@@ -21,7 +21,22 @@ extern "C"
 
 void FFTCorrelation::correlate(const int64_t *left, const int leftSize,
                                const int64_t *right, const int rightSize,
-                               float **out_correlated, int &out_size)
+                               int64_t *out_correlated)
+{
+    float correlatedFloat[leftSize+rightSize+1];
+    correlate(left, leftSize, right, rightSize, correlatedFloat);
+
+    // The correlation vector will have entries up to N (number of entries
+    // of the vector), so converting to integers will not lose that much
+    // of precision.
+    for (int i = 0; i < leftSize+rightSize+1; ++i) {
+        out_correlated[i] = correlatedFloat[i];
+    }
+}
+
+void FFTCorrelation::correlate(const int64_t *left, const int leftSize,
+                               const int64_t *right, const int rightSize,
+                               float *out_correlated)
 {
     QTime t;
     t.start();
@@ -33,14 +48,14 @@ void FFTCorrelation::correlate(const int64_t *left, const int leftSize,
     // Dividing by the max value is maybe not the best solution, but the
     // maximum value after correlation should not be larger than the longest
     // vector since each value should be at most 1
-    int64_t maxLeft = 0;
-    int64_t maxRight = 0;
-    for (int i = 0; i < leftSize; i++) {
+    int64_t maxLeft = 1;
+    int64_t maxRight = 1;
+    for (int i = 0; i < leftSize; ++i) {
         if (labs(left[i]) > maxLeft) {
             maxLeft = labs(left[i]);
         }
     }
-    for (int i = 0; i < rightSize; i++) {
+    for (int i = 0; i < rightSize; ++i) {
         if (labs(right[i]) > maxRight) {
             maxRight = labs(right[i]);
         }
@@ -49,22 +64,22 @@ void FFTCorrelation::correlate(const int64_t *left, const int leftSize,
 
     // One side needs to be reverted, since multiplication in frequency domain (fourier space)
     // calculates the convolution: \sum l[x]r[N-x] and not the correlation: \sum l[x]r[x]
-    for (int i = 0; i < leftSize; i++) {
-        leftF[leftSize-1 - i] = double(left[i])/maxLeft;
+    for (int i = 0; i < leftSize; ++i) {
+        leftF[i] = double(left[i])/maxLeft;
     }
-    for (int i = 0; i < rightSize; i++) {
-        rightF[i] = double(right[i])/maxRight;
+    for (int i = 0; i < rightSize; ++i) {
+        rightF[rightSize-1 - i] = double(right[i])/maxRight;
     }
 
     // Now we can convolve to get the correlation
-    convolute(leftF, leftSize, rightF, rightSize, out_correlated, out_size);
+    convolve(leftF, leftSize, rightF, rightSize, out_correlated);
 
     std::cout << "Correlation (FFT based) computed in " << t.elapsed() << " ms." << std::endl;
 }
 
-void FFTCorrelation::convolute(const float *left, const int leftSize,
+void FFTCorrelation::convolve(const float *left, const int leftSize,
                                const float *right, const int rightSize,
-                               float **out_convolved, int &out_size)
+                               float *out_convolved)
 {
     QTime time;
     time.start();
@@ -95,7 +110,7 @@ void FFTCorrelation::convolute(const float *left, const int leftSize,
     // Fill in the data into our new vectors with padding
     float leftData[size];
     float rightData[size];
-    *out_convolved = new float[size];
+    float convolved[size];
 
     std::fill(leftData, leftData+size, 0);
     std::fill(rightData, rightData+size, 0);
@@ -108,14 +123,19 @@ void FFTCorrelation::convolute(const float *left, const int leftSize,
     kiss_fftr(fftConfig, rightData, rightFFT);
 
     // Convolution in spacial domain is a multiplication in fourier domain. O(n).
-    for (int i = 0; i < size/2; i++) {
+    for (int i = 0; i < size/2; ++i) {
         correlatedFFT[i].r = leftFFT[i].r*rightFFT[i].r - leftFFT[i].i*rightFFT[i].i;
         correlatedFFT[i].i = leftFFT[i].r*rightFFT[i].i + leftFFT[i].i*rightFFT[i].r;
     }
 
-    // Inverse fourier tranformation to get the convolved data
-    kiss_fftri(ifftConfig, correlatedFFT, *out_convolved);
-    out_size = size;
+    // Inverse fourier tranformation to get the convolved data.
+    // Insert one element at the beginning to obtain the same result
+    // that we also get with the nested for loop correlation.
+    *out_convolved = 0;
+    int out_size = leftSize+rightSize+1;
+
+    kiss_fftri(ifftConfig, correlatedFFT, convolved);
+    std::copy(convolved, convolved+out_size-1, out_convolved+1);
 
     // Finally some cleanup.
     kiss_fftr_free(fftConfig);