A Sandcastle Documented Class Library
NeuQuant Class
NeuQuant Neural-Net Quantization Algorithm ------------------------------------------ Copyright (c) 1994 Anthony Dekker NEUQUANT Neural-Net quantization algorithm by Anthony Dekker, 1994. See "Kohonen neural networks for optimal colour quantization" in "Network: Computation in Neural Systems" Vol. 5 (1994) pp 351-367. for a discussion of the algorithm. Any party obtaining a copy of these files from the author, directly or indirectly, is granted, free of charge, a full and unrestricted irrevocable, world-wide, paid up, royalty-free, nonexclusive right and license to deal in this software and documentation files (the "Software"), including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons who receive copies from any such party to do so, with the only requirement being that this copyright notice remain intact. Ported to Java 12/00 K Weiner Modified by Simon Bridewell, June 2009: Downloaded from http://www.thinkedge.com/BlogEngine/file.axd?file=NGif_src2.zip Adapted by for FxCop code analysis compliance and documentation comments converted to .net XML comments. Updated to use .net 2.0 generics - use List instead of byte[]
Declaration Syntax
C#Visual BasicVisual C++
public class NeuQuant
Public Class NeuQuant
public ref class NeuQuant
All MembersConstructorsMethods

NeuQuant(Collection<(Of <(Byte>)>), Int32, Int32)
Constructor. Initialise network in range (0,0,0) to (255,255,255) and set parameters

Insertion sort of network and building of netindex[0..255] (to do after unbias)

Determines whether the specified Object is equal to the current Object.
(Inherited from Object.)
Allows an Object to attempt to free resources and perform other cleanup operations before the Object is reclaimed by garbage collection.
(Inherited from Object.)
Serves as a hash function for a particular type. GetHashCode()()() is suitable for use in hashing algorithms and data structures like a hash table.
(Inherited from Object.)
Gets the Type of the current instance.
(Inherited from Object.)
Main Learning Loop

Map(Int32, Int32, Int32)
Search for BGR values 0..255 (after net is unbiased) and return the index in the colour table of the colour closest to the supplied colour. TODO: consider accepting a Color rather than R,G,B integers.

Creates a shallow copy of the current Object.
(Inherited from Object.)
Calls the Learn, UnbiasNetwork and BuildIndex method and returns the ColorMap.

Returns a String that represents the current Object.
(Inherited from Object.)
Unbias network to give byte values 0..255 and record position i to prepare for sort

Inheritance Hierarchy

Assembly: GifComponents (Module: GifComponents) Version: 0.1.3594.26453