📄 neuquant.h
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/* NeuQuant Neural-Net Quantization Algorithm Interface
* ----------------------------------------------------
*
* 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.
*/
#include <stdio.h>
# ifdef __cplusplus
extern "C" {
# endif
#define netsize 256 /* number of colours used */
/* For 256 colours, fixed arrays need 8kb, plus space for the image
---------------------------------------------------------------- */
/* four primes near 500 - assume no image has a length so large */
/* that it is divisible by all four primes */
#define prime1 499
#define prime2 491
#define prime3 487
#define prime4 503
#define minpicturebytes (3*prime4) /* minimum size for input image */
/* Initialise network in range (0,0,0) to (255,255,255) and set parameters
----------------------------------------------------------------------- */
void initnet(unsigned char *thepic, int len, int sample);
/* Unbias network to give byte values 0..255 and record position i to prepare for sort
----------------------------------------------------------------------------------- */
void unbiasnet(); /* can edit this function to do output of colour map */
/* Output colour map
----------------- */
void writecolourmap(FILE *f);
void getcolourmap(unsigned char *Pal );
/* Insertion sort of network and building of netindex[0..255] (to do after unbias)
------------------------------------------------------------------------------- */
void inxbuild();
/* Search for BGR values 0..255 (after net is unbiased) and return colour index
---------------------------------------------------------------------------- */
int inxsearch(register int b, register int g, register int r);
/* Main Learning Loop
------------------ */
void learn();
/* Program Skeleton
----------------
[select samplefac in range 1..30]
[read image from input file]
pic = (unsigned char*) malloc(3*width*height);
initnet(pic,3*width*height,samplefac);
learn();
unbiasnet();
[write output image header, using writecolourmap(f)]
inxbuild();
write output image using inxsearch(b,g,r) */
# ifdef __cplusplus
}
# endif
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