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Try to avoid having unused palette items when the source image only uses a limited gamut region 

Warp each empty cluster's centroid onto the closest dataset item
This commit is contained in:
Vftdan 2024-10-03 10:18:02 +02:00
parent c91f4d79bd
commit 5f95f895d2
1 changed files with 17 additions and 3 deletions
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20
img2cpi.c
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@ -95,6 +95,8 @@ struct k_means_state {
float r, g, b; float r, g, b;
} sums; } sums;
size_t count; size_t count;
union color closest_present_item;
float closest_present_distance;
} *centroid_intermediate; } *centroid_intermediate;
size_t item_count; size_t item_count;
}; };
@ -683,6 +685,12 @@ struct k_means_state k_means_init(const struct image *image, struct palette *sta
.centroid_intermediate = calloc(cluster_count, sizeof(struct k_means_centroid_intermediate)), .centroid_intermediate = calloc(cluster_count, sizeof(struct k_means_centroid_intermediate)),
.item_count = item_count, .item_count = item_count,
}; };
if (state.centroid_intermediate) {
for (size_t i = 0; i < cluster_count; i++) {
state.centroid_intermediate[i].closest_present_item = starting_palette->colors[i];
state.centroid_intermediate[i].closest_present_distance = 1e20;
}
}
return state; return state;
} }
@ -697,11 +705,16 @@ bool k_means_iteration(struct k_means_state *state) {
int closest_cluster = 0; int closest_cluster = 0;
float closest_distance = 1e20; float closest_distance = 1e20;
for (int cluster = 0; cluster < state->clusters->count; cluster++) { for (int cluster = 0; cluster < state->clusters->count; cluster++) {
float dist = get_color_difference(state->clusters->colors[cluster], state->items->pixels[i]); union color item = state->items->pixels[i];
float dist = get_color_difference(state->clusters->colors[cluster], item);
if (dist <= closest_distance) { if (dist <= closest_distance) {
closest_distance = dist; closest_distance = dist;
closest_cluster = cluster; closest_cluster = cluster;
} }
if (dist <= state->centroid_intermediate[cluster].closest_present_distance) {
state->centroid_intermediate[cluster].closest_present_item = item;
state->centroid_intermediate[cluster].closest_present_distance = dist;
}
} }
if (!changed) { if (!changed) {
changed = state->predicted_cluster[i] != closest_cluster; changed = state->predicted_cluster[i] != closest_cluster;
@ -731,9 +744,10 @@ bool k_means_iteration(struct k_means_state *state) {
state->clusters->colors[i] = centroid; state->clusters->colors[i] = centroid;
} else { } else {
// No pixels are closest to this color // No pixels are closest to this color
// TODO: wiggle the centroid? // Warp the centroid onto the closest item
state->clusters->colors[i] = intermediate.closest_present_item;
} }
state->centroid_intermediate[i] = (struct k_means_centroid_intermediate) { .sums = {0, 0, 0}, .count = 0 }; state->centroid_intermediate[i] = (struct k_means_centroid_intermediate) { .sums = {0, 0, 0}, .count = 0, .closest_present_item = state->clusters->colors[i], .closest_present_distance = 1e20 };
} }
return changed; return changed;