static WEBP_INLINE
void DoGradientFilter(const uint8_t* in, int width, int height,
int stride, int inverse, uint8_t* out) {
const uint8_t* preds = (inverse ? out : in);
int h;
SANITY_CHECK(in, out);
// left prediction for top scan-line
out[0] = in[0];
PredictLine(in + 1, preds, out + 1, width - 1, inverse);
// Filter line-by-line.
for (h = 1; h < height; ++h) {
int w;
preds += stride;
in += stride;
out += stride;
// leftmost pixel: predict from above.
PredictLine(in, preds - stride, out, 1, inverse);
for (w = 1; w < width; ++w) {
const int pred = GradientPredictor(preds[w - 1],
preds[w - stride],
preds[w - stride - 1]);
out[w] = in[w] + (inverse ? pred : -pred);
}
}
}
WEBP_FILTER_TYPE EstimateBestFilter(const uint8_t* data,
int width, int height, int stride) {
int i, j;
int bins[WEBP_FILTER_LAST][SMAX];
memset(bins, 0, sizeof(bins));
// We only sample every other pixels. That's enough.
for (j = 2; j < height - 1; j += 2) {
const uint8_t* const p = data + j * stride;
int mean = p[0];
for (i = 2; i < width - 1; i += 2) {
const int diff0 = SDIFF(p[i], mean);
const int diff1 = SDIFF(p[i], p[i - 1]);
const int diff2 = SDIFF(p[i], p[i - width]);
const int grad_pred =
GradientPredictor(p[i - 1], p[i - width], p[i - width - 1]);
const int diff3 = SDIFF(p[i], grad_pred);
bins[WEBP_FILTER_NONE][diff0] = 1;
bins[WEBP_FILTER_HORIZONTAL][diff1] = 1;
bins[WEBP_FILTER_VERTICAL][diff2] = 1;
bins[WEBP_FILTER_GRADIENT][diff3] = 1;
mean = (3 * mean + p[i] + 2) >> 2;
}
}
{
int filter;
WEBP_FILTER_TYPE best_filter = WEBP_FILTER_NONE;
int best_score = 0x7fffffff;
for (filter = WEBP_FILTER_NONE; filter < WEBP_FILTER_LAST; ++filter) {
int score = 0;
for (i = 0; i < SMAX; ++i) {
if (bins[filter][i] > 0) {
score += i;
}
}
if (score < best_score) {
best_score = score;
best_filter = (WEBP_FILTER_TYPE)filter;
}
}
return best_filter;
}
}
static WEBP_INLINE void DoGradientFilter(const uint8_t* in,
int width, int height, int stride,
int row, int num_rows,
int inverse, uint8_t* out) {
const uint8_t* preds;
const size_t start_offset = row * stride;
const int last_row = row + num_rows;
SANITY_CHECK(in, out);
in += start_offset;
out += start_offset;
preds = inverse ? out : in;
// left prediction for top scan-line
if (row == 0) {
out[0] = in[0];
PredictLine(in + 1, preds, out + 1, width - 1, inverse);
row = 1;
preds += stride;
in += stride;
out += stride;
}
// Filter line-by-line.
while (row < last_row) {
int w;
// leftmost pixel: predict from above.
PredictLine(in, preds - stride, out, 1, inverse);
for (w = 1; w < width; ++w) {
const int pred = GradientPredictor(preds[w - 1],
preds[w - stride],
preds[w - stride - 1]);
out[w] = in[w] + (inverse ? pred : -pred);
}
++row;
preds += stride;
in += stride;
out += stride;
}
}