QuantizerCelebi class final

An image quantizer that improves on the quality of a standard K-Means algorithm by setting the K-Means initial state to the output of a Wu quantizer, instead of random centroids. Improves on speed by several optimizations, as implemented in Wsmeans, or Weighted Square Means, K-Means with those optimizations.

This algorithm was designed by M. Emre Celebi, and was found in their 2011 paper, Improving the Performance of K-Means for Color Quantization. https://arxiv.org/abs/1101.0395

Implemented types

• Quantizer

Constructors

QuantizerCelebi()

const

Properties

hashCode → int

The hash code for this object.

no setter, inherited

runtimeType → Type

A representation of the runtime type of the object.

no setter, inherited

Methods

noSuchMethod(Invocation invocation) → dynamic

Invoked when a nonexistent method or property is accessed.

inherited

quantize(List<int> pixels, int maxColors) → QuantizerResult

Reduce the number of colors needed to represented the input, minimizing the difference between the original image and the recolored image.

override

toString() → String

A string representation of this object.

inherited

Operators

operator ==(Object other) → bool

The equality operator.

inherited