X-Git-Url: https://git.nihav.org/?p=nihav.git;a=blobdiff_plain;f=nihav-core%2Fsrc%2Fscale%2Fpalette%2Felbg.rs;h=9a7d96701e764e38729778da71daa7af6c6c61a2;hp=300b3f1610b5dc33f8a52c05df64099e2e671344;hb=b191eef3e3e1b6bea510c7e64606d8442f974f8b;hpb=b36f412c24813b14cb2b1f8fd151863e2a49c1e2

diff --git a/nihav-core/src/scale/palette/elbg.rs b/nihav-core/src/scale/palette/elbg.rs
index 300b3f1..9a7d967 100644
--- a/nihav-core/src/scale/palette/elbg.rs
+++ b/nihav-core/src/scale/palette/elbg.rs
@@ -66,9 +66,6 @@ impl Cluster {
         }
     }
     fn calc_dist(&mut self) {
-        if self.count != 0 {
-            self.dist = (self.dist + self.count / 2) / self.count;
-        }
     }
 }
 
@@ -198,7 +195,7 @@ impl ELBG {
         clu1.calc_dist();
         clu0.dist + clu1.dist
     }
-    #[allow(clippy::cyclomatic_complexity)]
+    #[allow(clippy::cognitive_complexity)]
     pub fn quantise(&mut self, src: &[Pixel], dst: &mut [[u8; 3]; 256]) {
         if src.len() < 3 {
             return;
@@ -232,14 +229,14 @@ impl ELBG {
         let mut rng = RNG::new();
         let mut iterations = 0usize;
         let mut do_elbg_step = true;
-        while (iterations < 20) && (dist < prev_dist - prev_dist / 1000) {
+        while (iterations < 10) && (dist < prev_dist - prev_dist / 100) {
             prev_dist = dist;
             for i in 0..256 {
                 old_cb[i] = self.clusters[i].centroid;
                 self.clusters[i].reset();
             }
             // put pixels into the nearest clusters
-            indices.truncate(0);
+            indices.clear();
             for entry in entries.iter() {
                 let mut bestidx = 0;
                 let mut bestdist = std::u32::MAX;
@@ -270,8 +267,8 @@ impl ELBG {
             }
 
             let dmean = dist / 256;
-            low_u.truncate(0);
-            high_u.truncate(0);
+            low_u.clear();
+            high_u.clear();
             let mut used = [false; 256];
             for (i, cluster) in self.clusters.iter().enumerate() {
                 if cluster.dist < dmean {