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Replace doubles by floats in lossless misc cost estimations.

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Doubles are slower and use more RAM for no benefit.

Change-Id: I05b313576f9b33388c7c39d7fed8de84170c3753
This commit is contained in:
Vincent Rabaud
2022-04-14 16:19:19 +02:00
parent 42888f6c7c
commit a19a25bb03
10 changed files with 154 additions and 160 deletions
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12
src/enc/predictor_enc.c
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@ -32,10 +32,10 @@ static WEBP_INLINE int GetMin(int a, int b) { return (a > b) ? b : a; }
// Methods to calculate Entropy (Shannon).
static float PredictionCostSpatial(const int counts[256], int weight_0,
double exp_val) {
float exp_val) {
const int significant_symbols = 256 >> 4;
const double exp_decay_factor = 0.6;
double bits = weight_0 * counts[0];
const float exp_decay_factor = 0.6f;
float bits = weight_0 * counts[0];
int i;
for (i = 1; i < significant_symbols; ++i) {
bits += exp_val * (counts[i] + counts[256 - i]);
@ -47,9 +47,9 @@ static float PredictionCostSpatial(const int counts[256], int weight_0,
static float PredictionCostSpatialHistogram(const int accumulated[4][256],
const int tile[4][256]) {
int i;
double retval = 0;
float retval = 0.f;
for (i = 0; i < 4; ++i) {
const double kExpValue = 0.94;
const float kExpValue = 0.94f;
retval += PredictionCostSpatial(tile[i], 1, kExpValue);
retval += VP8LCombinedShannonEntropy(tile[i], accumulated[i]);
}
@ -543,7 +543,7 @@ static float PredictionCostCrossColor(const int accumulated[256],
const int counts[256]) {
// Favor low entropy, locally and globally.
// Favor small absolute values for PredictionCostSpatial
static const double kExpValue = 2.4;
static const float kExpValue = 2.4f;
return VP8LCombinedShannonEntropy(counts, accumulated) +
PredictionCostSpatial(counts, 3, kExpValue);
}