Write.+ * + * Three caveats: + *
+ * + *
+ * + *
+ * java.awt.AWTException: Grabber returned false: 192
+ *
+ * + * GIFEncoder is based upon gifsave.c, which was written and released + * by:
+ *
+ *
+ * Phone: +47 2 230539
+ * sverrehu@ifi.uio.no
+ *
+ * + * @param image The image to encode. The image must be + * completely loaded. + * @exception AWTException Will be thrown if the pixel grab fails. This + * can happen if Java runs out of memory. It may also indicate that the image + * contains more than 256 colors. + * */ + public GIFEncoder(Image image) throws AWTException { + width_ = (short)image.getWidth(null); + height_ = (short)image.getHeight(null); + + int values[] = new int[width_ * height_]; + PixelGrabber grabber = new PixelGrabber( + image, 0, 0, width_, height_, values, 0, width_); + + try { + if(grabber.grabPixels() != true) + throw new AWTException("Grabber returned false: " + + grabber.status()); + } + catch (InterruptedException e) { ; } + + byte r[][] = new byte[width_][height_]; + byte g[][] = new byte[width_][height_]; + byte b[][] = new byte[width_][height_]; + int index = 0; + for (int y = 0; y < height_; ++y) + for (int x = 0; x < width_; ++x) { + r[x][y] = (byte)((values[index] >> 16) & 0xFF); + g[x][y] = (byte)((values[index] >> 8) & 0xFF); + b[x][y] = (byte)((values[index]) & 0xFF); + ++index; + } + ToIndexedColor(r, g, b); + } + +/** + * Construct a GIFEncoder. The constructor will convert the image to + * an indexed color array. This may take some time.
+ * + * Each array stores intensity values for the image. In other words, + * r[x][y] refers to the red intensity of the pixel at column x, row + * y.
+ * + * @param r An array containing the red intensity values. + * @param g An array containing the green intensity values. + * @param b An array containing the blue intensity values. + * + * @exception AWTException Will be thrown if the image contains more than + * 256 colors. + * */ + public GIFEncoder(byte r[][], byte g[][], byte b[][]) throws AWTException { + width_ = (short)(r.length); + height_ = (short)(r[0].length); + + ToIndexedColor(r, g, b); + } + +/** + * Writes the image out to a stream in the GIF file format. This will + * be a single GIF87a image, non-interlaced, with no background color. + * This may take some time.
+ * + * @param output The stream to output to. This should probably be a + * buffered stream. + * + * @exception IOException Will be thrown if a write operation fails. + * */ + public void Write(OutputStream output) throws IOException { + BitUtils.WriteString(output, "GIF87a"); + + ScreenDescriptor sd = new ScreenDescriptor(width_, height_, + numColors_); + sd.Write(output); + + output.write(colors_, 0, colors_.length); + + ImageDescriptor id = new ImageDescriptor(width_, height_, ','); + id.Write(output); + + byte codesize = BitUtils.BitsNeeded(numColors_); + if (codesize == 1) + ++codesize; + output.write(codesize); + + LZWCompressor.LZWCompress(output, codesize, pixels_); + output.write(0); + + id = new ImageDescriptor((byte)0, (byte)0, ';'); + id.Write(output); + output.flush(); + } + + void ToIndexedColor(byte r[][], byte g[][], + byte b[][]) throws AWTException { + pixels_ = new byte[width_ * height_]; + colors_ = new byte[256 * 3]; + int colornum = 0; + for (int x = 0; x < width_; ++x) { + for (int y = 0; y < height_; ++y) { + int search; + for (search = 0; search < colornum; ++search) + if (colors_[search * 3] == r[x][y] && + colors_[search * 3 + 1] == g[x][y] && + colors_[search * 3 + 2] == b[x][y]) + break; + + if (search > 255) + throw new AWTException("Too many colors."); + + pixels_[y * width_ + x] = (byte)search; + + if (search == colornum) { + colors_[search * 3] = r[x][y]; + colors_[search * 3 + 1] = g[x][y]; + colors_[search * 3 + 2] = b[x][y]; + ++colornum; + } + } + } + numColors_ = 1 << BitUtils.BitsNeeded(colornum); + byte copy[] = new byte[numColors_ * 3]; + System.arraycopy(colors_, 0, copy, 0, numColors_ * 3); + colors_ = copy; + } + +} + +class BitFile { + OutputStream output_; + byte buffer_[]; + int index_, bitsLeft_; + + public BitFile(OutputStream output) { + output_ = output; + buffer_ = new byte[256]; + index_ = 0; + bitsLeft_ = 8; + } + + public void Flush() throws IOException { + int numBytes = index_ + (bitsLeft_ == 8 ? 0 : 1); + if (numBytes > 0) { + output_.write(numBytes); + output_.write(buffer_, 0, numBytes); + buffer_[0] = 0; + index_ = 0; + bitsLeft_ = 8; + } + } + + public void WriteBits(int bits, int numbits) throws IOException { + int bitsWritten = 0; + int numBytes = 255; + do { + if ((index_ == 254 && bitsLeft_ == 0) || index_ > 254) { + output_.write(numBytes); + output_.write(buffer_, 0, numBytes); + + buffer_[0] = 0; + index_ = 0; + bitsLeft_ = 8; + } + + if (numbits <= bitsLeft_) { + buffer_[index_] |= (bits & ((1 << numbits) - 1)) << + (8 - bitsLeft_); + bitsWritten += numbits; + bitsLeft_ -= numbits; + numbits = 0; + } + else { + buffer_[index_] |= (bits & ((1 << bitsLeft_) - 1)) << + (8 - bitsLeft_); + bitsWritten += bitsLeft_; + bits >>= bitsLeft_; + numbits -= bitsLeft_; + buffer_[++index_] = 0; + bitsLeft_ = 8; + } + } while (numbits != 0); + } +} + +class LZWStringTable { + private final static int RES_CODES = 2; + private final static short HASH_FREE = (short)0xFFFF; + private final static short NEXT_FIRST = (short)0xFFFF; + private final static int MAXBITS = 12; + private final static int MAXSTR = (1 << MAXBITS); + private final static short HASHSIZE = 9973; + private final static short HASHSTEP = 2039; + + byte strChr_[]; + short strNxt_[]; + short strHsh_[]; + short numStrings_; + + public LZWStringTable() { + strChr_ = new byte[MAXSTR]; + strNxt_ = new short[MAXSTR]; + strHsh_ = new short[HASHSIZE]; + } + + public int AddCharString(short index, byte b) { + int hshidx; + + if (numStrings_ >= MAXSTR) + return 0xFFFF; + + hshidx = Hash(index, b); + while (strHsh_[hshidx] != HASH_FREE) + hshidx = (hshidx + HASHSTEP) % HASHSIZE; + + strHsh_[hshidx] = numStrings_; + strChr_[numStrings_] = b; + strNxt_[numStrings_] = (index != HASH_FREE) ? index : NEXT_FIRST; + + return numStrings_++; + } + + public short FindCharString(short index, byte b) { + int hshidx, nxtidx; + + if (index == HASH_FREE) + return b; + + hshidx = Hash(index, b); + while ((nxtidx = strHsh_[hshidx]) != HASH_FREE) { + if (strNxt_[nxtidx] == index && strChr_[nxtidx] == b) + return (short)nxtidx; + hshidx = (hshidx + HASHSTEP) % HASHSIZE; + } + + return (short)0xFFFF; + } + + public void ClearTable(int codesize) { + numStrings_ = 0; + + for (int q = 0; q < HASHSIZE; q++) { + strHsh_[q] = HASH_FREE; + } + + int w = (1 << codesize) + RES_CODES; + for (int q = 0; q < w; q++) + AddCharString((short)0xFFFF, (byte)q); + } + + static public int Hash(short index, byte lastbyte) { + return ((int)((short)(lastbyte << 8) ^ index) & 0xFFFF) % HASHSIZE; + } +} + +class LZWCompressor { + + public static void LZWCompress(OutputStream output, int codesize, + byte toCompress[]) throws IOException { + byte c; + short index; + int clearcode, endofinfo, numbits, limit, errcode; + short prefix = (short)0xFFFF; + + BitFile bitFile = new BitFile(output); + LZWStringTable strings = new LZWStringTable(); + + clearcode = 1 << codesize; + endofinfo = clearcode + 1; + + numbits = codesize + 1; + limit = (1 << numbits) - 1; + + strings.ClearTable(codesize); + bitFile.WriteBits(clearcode, numbits); + + for (int loop = 0; loop < toCompress.length; ++loop) { + c = toCompress[loop]; + if ((index = strings.FindCharString(prefix, c)) != -1) + prefix = index; + else { + bitFile.WriteBits(prefix, numbits); + if (strings.AddCharString(prefix, c) > limit) { + if (++numbits > 12) { + bitFile.WriteBits(clearcode, numbits - 1); + strings.ClearTable(codesize); + numbits = codesize + 1; + } + limit = (1 << numbits) - 1; + } + + prefix = (short)((short)c & 0xFF); + } + } + + if (prefix != -1) + bitFile.WriteBits(prefix, numbits); + + bitFile.WriteBits(endofinfo, numbits); + bitFile.Flush(); + } +} + +class ScreenDescriptor { + public short localScreenWidth_, localScreenHeight_; + private byte byte_; + public byte backgroundColorIndex_, pixelAspectRatio_; + + public ScreenDescriptor(short width, short height, int numColors) { + localScreenWidth_ = width; + localScreenHeight_ = height; + SetGlobalColorTableSize((byte)(BitUtils.BitsNeeded(numColors) - 1)); + SetGlobalColorTableFlag((byte)1); + SetSortFlag((byte)0); + SetColorResolution((byte)7); + backgroundColorIndex_ = 0; + pixelAspectRatio_ = 0; + } + + public void Write(OutputStream output) throws IOException { + BitUtils.WriteWord(output, localScreenWidth_); + BitUtils.WriteWord(output, localScreenHeight_); + output.write(byte_); + output.write(backgroundColorIndex_); + output.write(pixelAspectRatio_); + } + + public void SetGlobalColorTableSize(byte num) { + byte_ |= (num & 7); + } + + public void SetSortFlag(byte num) { + byte_ |= (num & 1) << 3; + } + + public void SetColorResolution(byte num) { + byte_ |= (num & 7) << 4; + } + + public void SetGlobalColorTableFlag(byte num) { + byte_ |= (num & 1) << 7; + } +} + +class ImageDescriptor { + public byte separator_; + public short leftPosition_, topPosition_, width_, height_; + private byte byte_; + + public ImageDescriptor(short width, short height, char separator) { + separator_ = (byte)separator; + leftPosition_ = 0; + topPosition_ = 0; + width_ = width; + height_ = height; + SetLocalColorTableSize((byte)0); + SetReserved((byte)0); + SetSortFlag((byte)0); + SetInterlaceFlag((byte)0); + SetLocalColorTableFlag((byte)0); + } + + public void Write(OutputStream output) throws IOException { + output.write(separator_); + BitUtils.WriteWord(output, leftPosition_); + BitUtils.WriteWord(output, topPosition_); + BitUtils.WriteWord(output, width_); + BitUtils.WriteWord(output, height_); + output.write(byte_); + } + + public void SetLocalColorTableSize(byte num) { + byte_ |= (num & 7); + } + + public void SetReserved(byte num) { + byte_ |= (num & 3) << 3; + } + + public void SetSortFlag(byte num) { + byte_ |= (num & 1) << 5; + } + + public void SetInterlaceFlag(byte num) { + byte_ |= (num & 1) << 6; + } + + public void SetLocalColorTableFlag(byte num) { + byte_ |= (num & 1) << 7; + } +} + +class BitUtils { + public static byte BitsNeeded(int n) { + byte ret = 1; + + if (n-- == 0) + return 0; + + while ((n >>= 1) != 0) + ++ret; + + return ret; + } + + public static void WriteWord(OutputStream output, + short w) throws IOException { + output.write(w & 0xFF); + output.write((w >> 8) & 0xFF); + } + + static void WriteString(OutputStream output, + String string) throws IOException { + for (int loop = 0; loop < string.length(); ++loop) + output.write((byte)(string.charAt(loop))); + } +} diff --git a/src/helma/image/Quantize.java b/src/helma/image/Quantize.java new file mode 100644 index 00000000..3666e620 --- /dev/null +++ b/src/helma/image/Quantize.java @@ -0,0 +1,701 @@ +/* + * @(#)Quantize.java 0.90 9/19/00 Adam Doppelt + */ +package helma.image; + +/** + * An efficient color quantization algorithm, adapted from the C++ + * implementation quantize.c in ImageMagick. The pixels for + * an image are placed into an oct tree. The oct tree is reduced in + * size, and the pixels from the original image are reassigned to the + * nodes in the reduced tree.
+ * + * Here is the copyright notice from ImageMagick: + * + *
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% Permission is hereby granted, free of charge, to any person obtaining a %
+% copy of this software and associated documentation files ("ImageMagick"), %
+% to deal in ImageMagick without restriction, including without limitation %
+% the rights to use, copy, modify, merge, publish, distribute, sublicense, %
+% and/or sell copies of ImageMagick, and to permit persons to whom the %
+% ImageMagick is furnished to do so, subject to the following conditions: %
+% %
+% The above copyright notice and this permission notice shall be included in %
+% all copies or substantial portions of ImageMagick. %
+% %
+% The software is provided "as is", without warranty of any kind, express or %
+% implied, including but not limited to the warranties of merchantability, %
+% fitness for a particular purpose and noninfringement. In no event shall %
+% E. I. du Pont de Nemours and Company be liable for any claim, damages or %
+% other liability, whether in an action of contract, tort or otherwise, %
+% arising from, out of or in connection with ImageMagick or the use or other %
+% dealings in ImageMagick. %
+% %
+% Except as contained in this notice, the name of the E. I. du Pont de %
+% Nemours and Company shall not be used in advertising or otherwise to %
+% promote the sale, use or other dealings in ImageMagick without prior %
+% written authorization from the E. I. du Pont de Nemours and Company. %
+% %
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+ *
+ *
+ * @version 0.90 19 Sep 2000
+ * @author Adam Doppelt
+ */
+public class Quantize {
+
+/*
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% %
+% %
+% %
+% QQQ U U AAA N N TTTTT IIIII ZZZZZ EEEEE %
+% Q Q U U A A NN N T I ZZ E %
+% Q Q U U AAAAA N N N T I ZZZ EEEEE %
+% Q QQ U U A A N NN T I ZZ E %
+% QQQQ UUU A A N N T IIIII ZZZZZ EEEEE %
+% %
+% %
+% Reduce the Number of Unique Colors in an Image %
+% %
+% %
+% Software Design %
+% John Cristy %
+% July 1992 %
+% %
+% %
+% Copyright 1998 E. I. du Pont de Nemours and Company %
+% %
+% Permission is hereby granted, free of charge, to any person obtaining a %
+% copy of this software and associated documentation files ("ImageMagick"), %
+% to deal in ImageMagick without restriction, including without limitation %
+% the rights to use, copy, modify, merge, publish, distribute, sublicense, %
+% and/or sell copies of ImageMagick, and to permit persons to whom the %
+% ImageMagick is furnished to do so, subject to the following conditions: %
+% %
+% The above copyright notice and this permission notice shall be included in %
+% all copies or substantial portions of ImageMagick. %
+% %
+% The software is provided "as is", without warranty of any kind, express or %
+% implied, including but not limited to the warranties of merchantability, %
+% fitness for a particular purpose and noninfringement. In no event shall %
+% E. I. du Pont de Nemours and Company be liable for any claim, damages or %
+% other liability, whether in an action of contract, tort or otherwise, %
+% arising from, out of or in connection with ImageMagick or the use or other %
+% dealings in ImageMagick. %
+% %
+% Except as contained in this notice, the name of the E. I. du Pont de %
+% Nemours and Company shall not be used in advertising or otherwise to %
+% promote the sale, use or other dealings in ImageMagick without prior %
+% written authorization from the E. I. du Pont de Nemours and Company. %
+% %
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%
+% Realism in computer graphics typically requires using 24 bits/pixel to
+% generate an image. Yet many graphic display devices do not contain
+% the amount of memory necessary to match the spatial and color
+% resolution of the human eye. The QUANTIZE program takes a 24 bit
+% image and reduces the number of colors so it can be displayed on
+% raster device with less bits per pixel. In most instances, the
+% quantized image closely resembles the original reference image.
+%
+% A reduction of colors in an image is also desirable for image
+% transmission and real-time animation.
+%
+% Function Quantize takes a standard RGB or monochrome images and quantizes
+% them down to some fixed number of colors.
+%
+% For purposes of color allocation, an image is a set of n pixels, where
+% each pixel is a point in RGB space. RGB space is a 3-dimensional
+% vector space, and each pixel, pi, is defined by an ordered triple of
+% red, green, and blue coordinates, (ri, gi, bi).
+%
+% Each primary color component (red, green, or blue) represents an
+% intensity which varies linearly from 0 to a maximum value, cmax, which
+% corresponds to full saturation of that color. Color allocation is
+% defined over a domain consisting of the cube in RGB space with
+% opposite vertices at (0,0,0) and (cmax,cmax,cmax). QUANTIZE requires
+% cmax = 255.
+%
+% The algorithm maps this domain onto a tree in which each node
+% represents a cube within that domain. In the following discussion
+% these cubes are defined by the coordinate of two opposite vertices:
+% The vertex nearest the origin in RGB space and the vertex farthest
+% from the origin.
+%
+% The tree's root node represents the the entire domain, (0,0,0) through
+% (cmax,cmax,cmax). Each lower level in the tree is generated by
+% subdividing one node's cube into eight smaller cubes of equal size.
+% This corresponds to bisecting the parent cube with planes passing
+% through the midpoints of each edge.
+%
+% The basic algorithm operates in three phases: Classification,
+% Reduction, and Assignment. Classification builds a color
+% description tree for the image. Reduction collapses the tree until
+% the number it represents, at most, the number of colors desired in the
+% output image. Assignment defines the output image's color map and
+% sets each pixel's color by reclassification in the reduced tree.
+% Our goal is to minimize the numerical discrepancies between the original
+% colors and quantized colors (quantization error).
+%
+% Classification begins by initializing a color description tree of
+% sufficient depth to represent each possible input color in a leaf.
+% However, it is impractical to generate a fully-formed color
+% description tree in the classification phase for realistic values of
+% cmax. If colors components in the input image are quantized to k-bit
+% precision, so that cmax= 2k-1, the tree would need k levels below the
+% root node to allow representing each possible input color in a leaf.
+% This becomes prohibitive because the tree's total number of nodes is
+% 1 + sum(i=1,k,8k).
+%
+% A complete tree would require 19,173,961 nodes for k = 8, cmax = 255.
+% Therefore, to avoid building a fully populated tree, QUANTIZE: (1)
+% Initializes data structures for nodes only as they are needed; (2)
+% Chooses a maximum depth for the tree as a function of the desired
+% number of colors in the output image (currently log2(colormap size)).
+%
+% For each pixel in the input image, classification scans downward from
+% the root of the color description tree. At each level of the tree it
+% identifies the single node which represents a cube in RGB space
+% containing the pixel's color. It updates the following data for each
+% such node:
+%
+% n1: Number of pixels whose color is contained in the RGB cube
+% which this node represents;
+%
+% n2: Number of pixels whose color is not represented in a node at
+% lower depth in the tree; initially, n2 = 0 for all nodes except
+% leaves of the tree.
+%
+% Sr, Sg, Sb: Sums of the red, green, and blue component values for
+% all pixels not classified at a lower depth. The combination of
+% these sums and n2 will ultimately characterize the mean color of a
+% set of pixels represented by this node.
+%
+% E: The distance squared in RGB space between each pixel contained
+% within a node and the nodes' center. This represents the quantization
+% error for a node.
+%
+% Reduction repeatedly prunes the tree until the number of nodes with
+% n2 > 0 is less than or equal to the maximum number of colors allowed
+% in the output image. On any given iteration over the tree, it selects
+% those nodes whose E count is minimal for pruning and merges their
+% color statistics upward. It uses a pruning threshold, Ep, to govern
+% node selection as follows:
+%
+% Ep = 0
+% while number of nodes with (n2 > 0) > required maximum number of colors
+% prune all nodes such that E <= Ep
+% Set Ep to minimum E in remaining nodes
+%
+% This has the effect of minimizing any quantization error when merging
+% two nodes together.
+%
+% When a node to be pruned has offspring, the pruning procedure invokes
+% itself recursively in order to prune the tree from the leaves upward.
+% n2, Sr, Sg, and Sb in a node being pruned are always added to the
+% corresponding data in that node's parent. This retains the pruned
+% node's color characteristics for later averaging.
+%
+% For each node, n2 pixels exist for which that node represents the
+% smallest volume in RGB space containing those pixel's colors. When n2
+% > 0 the node will uniquely define a color in the output image. At the
+% beginning of reduction, n2 = 0 for all nodes except a the leaves of
+% the tree which represent colors present in the input image.
+%
+% The other pixel count, n1, indicates the total number of colors
+% within the cubic volume which the node represents. This includes n1 -
+% n2 pixels whose colors should be defined by nodes at a lower level in
+% the tree.
+%
+% Assignment generates the output image from the pruned tree. The
+% output image consists of two parts: (1) A color map, which is an
+% array of color descriptions (RGB triples) for each color present in
+% the output image; (2) A pixel array, which represents each pixel as
+% an index into the color map array.
+%
+% First, the assignment phase makes one pass over the pruned color
+% description tree to establish the image's color map. For each node
+% with n2 > 0, it divides Sr, Sg, and Sb by n2 . This produces the
+% mean color of all pixels that classify no lower than this node. Each
+% of these colors becomes an entry in the color map.
+%
+% Finally, the assignment phase reclassifies each pixel in the pruned
+% tree to identify the deepest node containing the pixel's color. The
+% pixel's value in the pixel array becomes the index of this node's mean
+% color in the color map.
+%
+% With the permission of USC Information Sciences Institute, 4676 Admiralty
+% Way, Marina del Rey, California 90292, this code was adapted from module
+% ALCOLS written by Paul Raveling.
+%
+% The names of ISI and USC are not used in advertising or publicity
+% pertaining to distribution of the software without prior specific
+% written permission from ISI.
+%
+*/
+
+ final static boolean QUICK = true;
+
+ final static int MAX_RGB = 255;
+ final static int MAX_NODES = 266817;
+ final static int MAX_TREE_DEPTH = 8;
+
+ // these are precomputed in advance
+ static int SQUARES[];
+ static int SHIFT[];
+
+ static {
+ SQUARES = new int[MAX_RGB + MAX_RGB + 1];
+ for (int i= -MAX_RGB; i <= MAX_RGB; i++) {
+ SQUARES[i + MAX_RGB] = i * i;
+ }
+
+ SHIFT = new int[MAX_TREE_DEPTH + 1];
+ for (int i = 0; i < MAX_TREE_DEPTH + 1; ++i) {
+ SHIFT[i] = 1 << (15 - i);
+ }
+ }
+
+ /**
+ * Reduce the image to the given number of colors. The pixels are
+ * reduced in place.
+ * @return The new color palette.
+ */
+ public static int[] quantizeImage(int pixels[][], int max_colors) {
+ Cube cube = new Cube(pixels, max_colors);
+ cube.classification();
+ cube.reduction();
+ cube.assignment();
+ return cube.colormap;
+ }
+
+ static class Cube {
+ int pixels[][];
+ int max_colors;
+ int colormap[];
+
+ Node root;
+ int depth;
+
+ // counter for the number of colors in the cube. this gets
+ // recalculated often.
+ int colors;
+
+ // counter for the number of nodes in the tree
+ int nodes;
+
+ Cube(int pixels[][], int max_colors) {
+ this.pixels = pixels;
+ this.max_colors = max_colors;
+
+ int i = max_colors;
+ // tree_depth = log max_colors
+ // 4
+ for (depth = 1; i != 0; depth++) {
+ i /= 4;
+ }
+ if (depth > 1) {
+ --depth;
+ }
+ if (depth > MAX_TREE_DEPTH) {
+ depth = MAX_TREE_DEPTH;
+ } else if (depth < 2) {
+ depth = 2;
+ }
+
+ root = new Node(this);
+ }
+
+ /*
+ * Procedure Classification begins by initializing a color
+ * description tree of sufficient depth to represent each
+ * possible input color in a leaf. However, it is impractical
+ * to generate a fully-formed color description tree in the
+ * classification phase for realistic values of cmax. If
+ * colors components in the input image are quantized to k-bit
+ * precision, so that cmax= 2k-1, the tree would need k levels
+ * below the root node to allow representing each possible
+ * input color in a leaf. This becomes prohibitive because the
+ * tree's total number of nodes is 1 + sum(i=1,k,8k).
+ *
+ * A complete tree would require 19,173,961 nodes for k = 8,
+ * cmax = 255. Therefore, to avoid building a fully populated
+ * tree, QUANTIZE: (1) Initializes data structures for nodes
+ * only as they are needed; (2) Chooses a maximum depth for
+ * the tree as a function of the desired number of colors in
+ * the output image (currently log2(colormap size)).
+ *
+ * For each pixel in the input image, classification scans
+ * downward from the root of the color description tree. At
+ * each level of the tree it identifies the single node which
+ * represents a cube in RGB space containing It updates the
+ * following data for each such node:
+ *
+ * number_pixels : Number of pixels whose color is contained
+ * in the RGB cube which this node represents;
+ *
+ * unique : Number of pixels whose color is not represented
+ * in a node at lower depth in the tree; initially, n2 = 0
+ * for all nodes except leaves of the tree.
+ *
+ * total_red/green/blue : Sums of the red, green, and blue
+ * component values for all pixels not classified at a lower
+ * depth. The combination of these sums and n2 will
+ * ultimately characterize the mean color of a set of pixels
+ * represented by this node.
+ */
+ void classification() {
+ int pixels[][] = this.pixels;
+
+ int width = pixels.length;
+ int height = pixels[0].length;
+
+ // convert to indexed color
+ for (int x = width; x-- > 0; ) {
+ for (int y = height; y-- > 0; ) {
+ int pixel = pixels[x][y];
+ int red = (pixel >> 16) & 0xFF;
+ int green = (pixel >> 8) & 0xFF;
+ int blue = (pixel >> 0) & 0xFF;
+
+ // a hard limit on the number of nodes in the tree
+ if (nodes > MAX_NODES) {
+ System.out.println("pruning");
+ root.pruneLevel();
+ --depth;
+ }
+
+ // walk the tree to depth, increasing the
+ // number_pixels count for each node
+ Node node = root;
+ for (int level = 1; level <= depth; ++level) {
+ int id = (((red > node.mid_red ? 1 : 0) << 0) |
+ ((green > node.mid_green ? 1 : 0) << 1) |
+ ((blue > node.mid_blue ? 1 : 0) << 2));
+ if (node.child[id] == null) {
+ new Node(node, id, level);
+ }
+ node = node.child[id];
+ node.number_pixels += SHIFT[level];
+ }
+
+ ++node.unique;
+ node.total_red += red;
+ node.total_green += green;
+ node.total_blue += blue;
+ }
+ }
+ }
+
+ /*
+ * reduction repeatedly prunes the tree until the number of
+ * nodes with unique > 0 is less than or equal to the maximum
+ * number of colors allowed in the output image.
+ *
+ * When a node to be pruned has offspring, the pruning
+ * procedure invokes itself recursively in order to prune the
+ * tree from the leaves upward. The statistics of the node
+ * being pruned are always added to the corresponding data in
+ * that node's parent. This retains the pruned node's color
+ * characteristics for later averaging.
+ */
+ void reduction() {
+ int threshold = 1;
+ while (colors > max_colors) {
+ colors = 0;
+ threshold = root.reduce(threshold, Integer.MAX_VALUE);
+ }
+ }
+
+ /**
+ * The result of a closest color search.
+ */
+ static class Search {
+ int distance;
+ int color_number;
+ }
+
+ /*
+ * Procedure assignment generates the output image from the
+ * pruned tree. The output image consists of two parts: (1) A
+ * color map, which is an array of color descriptions (RGB
+ * triples) for each color present in the output image; (2) A
+ * pixel array, which represents each pixel as an index into
+ * the color map array.
+ *
+ * First, the assignment phase makes one pass over the pruned
+ * color description tree to establish the image's color map.
+ * For each node with n2 > 0, it divides Sr, Sg, and Sb by n2.
+ * This produces the mean color of all pixels that classify no
+ * lower than this node. Each of these colors becomes an entry
+ * in the color map.
+ *
+ * Finally, the assignment phase reclassifies each pixel in
+ * the pruned tree to identify the deepest node containing the
+ * pixel's color. The pixel's value in the pixel array becomes
+ * the index of this node's mean color in the color map.
+ */
+ void assignment() {
+ colormap = new int[colors];
+
+ colors = 0;
+ root.colormap();
+
+ int pixels[][] = this.pixels;
+
+ int width = pixels.length;
+ int height = pixels[0].length;
+
+ Search search = new Search();
+
+ // convert to indexed color
+ for (int x = width; x-- > 0; ) {
+ for (int y = height; y-- > 0; ) {
+ int pixel = pixels[x][y];
+ int red = (pixel >> 16) & 0xFF;
+ int green = (pixel >> 8) & 0xFF;
+ int blue = (pixel >> 0) & 0xFF;
+
+ // walk the tree to find the cube containing that color
+ Node node = root;
+ for ( ; ; ) {
+ int id = (((red > node.mid_red ? 1 : 0) << 0) |
+ ((green > node.mid_green ? 1 : 0) << 1) |
+ ((blue > node.mid_blue ? 1 : 0) << 2) );
+ if (node.child[id] == null) {
+ break;
+ }
+ node = node.child[id];
+ }
+
+ if (QUICK) {
+ // if QUICK is set, just use that
+ // node. Strictly speaking, this isn't
+ // necessarily best match.
+ pixels[x][y] = node.color_number;
+ } else {
+ // Find the closest color.
+ search.distance = Integer.MAX_VALUE;
+ node.parent.closestColor(red, green, blue, search);
+ pixels[x][y] = search.color_number;
+ }
+ }
+ }
+ }
+
+ /**
+ * A single Node in the tree.
+ */
+ static class Node {
+ Cube cube;
+
+ // parent node
+ Node parent;
+
+ // child nodes
+ Node child[];
+ int nchild;
+
+ // our index within our parent
+ int id;
+ // our level within the tree
+ int level;
+ // our color midpoint
+ int mid_red;
+ int mid_green;
+ int mid_blue;
+
+ // the pixel count for this node and all children
+ int number_pixels;
+
+ // the pixel count for this node
+ int unique;
+ // the sum of all pixels contained in this node
+ int total_red;
+ int total_green;
+ int total_blue;
+
+ // used to build the colormap
+ int color_number;
+
+ Node(Cube cube) {
+ this.cube = cube;
+ this.parent = this;
+ this.child = new Node[8];
+ this.id = 0;
+ this.level = 0;
+
+ this.number_pixels = Integer.MAX_VALUE;
+
+ this.mid_red = (MAX_RGB + 1) >> 1;
+ this.mid_green = (MAX_RGB + 1) >> 1;
+ this.mid_blue = (MAX_RGB + 1) >> 1;
+ }
+
+ Node(Node parent, int id, int level) {
+ this.cube = parent.cube;
+ this.parent = parent;
+ this.child = new Node[8];
+ this.id = id;
+ this.level = level;
+
+ // add to the cube
+ ++cube.nodes;
+ if (level == cube.depth) {
+ ++cube.colors;
+ }
+
+ // add to the parent
+ ++parent.nchild;
+ parent.child[id] = this;
+
+ // figure out our midpoint
+ int bi = (1 << (MAX_TREE_DEPTH - level)) >> 1;
+ mid_red = parent.mid_red + ((id & 1) > 0 ? bi : -bi);
+ mid_green = parent.mid_green + ((id & 2) > 0 ? bi : -bi);
+ mid_blue = parent.mid_blue + ((id & 4) > 0 ? bi : -bi);
+ }
+
+ /**
+ * Remove this child node, and make sure our parent
+ * absorbs our pixel statistics.
+ */
+ void pruneChild() {
+ --parent.nchild;
+ parent.unique += unique;
+ parent.total_red += total_red;
+ parent.total_green += total_green;
+ parent.total_blue += total_blue;
+ parent.child[id] = null;
+ --cube.nodes;
+ cube = null;
+ parent = null;
+ }
+
+ /**
+ * Prune the lowest layer of the tree.
+ */
+ void pruneLevel() {
+ if (nchild != 0) {
+ for (int id = 0; id < 8; id++) {
+ if (child[id] != null) {
+ child[id].pruneLevel();
+ }
+ }
+ }
+ if (level == cube.depth) {
+ pruneChild();
+ }
+ }
+
+ /**
+ * Remove any nodes that have fewer than threshold
+ * pixels. Also, as long as we're walking the tree:
+ *
+ * - figure out the color with the fewest pixels
+ * - recalculate the total number of colors in the tree
+ */
+ int reduce(int threshold, int next_threshold) {
+ if (nchild != 0) {
+ for (int id = 0; id < 8; id++) {
+ if (child[id] != null) {
+ next_threshold = child[id].reduce(threshold, next_threshold);
+ }
+ }
+ }
+ if (number_pixels <= threshold) {
+ pruneChild();
+ } else {
+ if (unique != 0) {
+ cube.colors++;
+ }
+ if (number_pixels < next_threshold) {
+ next_threshold = number_pixels;
+ }
+ }
+ return next_threshold;
+ }
+
+ /*
+ * colormap traverses the color cube tree and notes each
+ * colormap entry. A colormap entry is any node in the
+ * color cube tree where the number of unique colors is
+ * not zero.
+ */
+ void colormap() {
+ if (nchild != 0) {
+ for (int id = 0; id < 8; id++) {
+ if (child[id] != null) {
+ child[id].colormap();
+ }
+ }
+ }
+ if (unique != 0) {
+ int r = ((total_red + (unique >> 1)) / unique);
+ int g = ((total_green + (unique >> 1)) / unique);
+ int b = ((total_blue + (unique >> 1)) / unique);
+ cube.colormap[cube.colors] = ((( 0xFF) << 24) |
+ ((r & 0xFF) << 16) |
+ ((g & 0xFF) << 8) |
+ ((b & 0xFF) << 0));
+ color_number = cube.colors++;
+ }
+ }
+
+ /* ClosestColor traverses the color cube tree at a
+ * particular node and determines which colormap entry
+ * best represents the input color.
+ */
+ void closestColor(int red, int green, int blue, Search search) {
+ if (nchild != 0) {
+ for (int id = 0; id < 8; id++) {
+ if (child[id] != null) {
+ child[id].closestColor(red, green, blue, search);
+ }
+ }
+ }
+
+ if (unique != 0) {
+ int color = cube.colormap[color_number];
+ int distance = distance(color, red, green, blue);
+ if (distance < search.distance) {
+ search.distance = distance;
+ search.color_number = color_number;
+ }
+ }
+ }
+
+ /**
+ * Figure out the distance between this node and som color.
+ */
+ final static int distance(int color, int r, int g, int b) {
+ return (SQUARES[((color >> 16) & 0xFF) - r + MAX_RGB] +
+ SQUARES[((color >> 8) & 0xFF) - g + MAX_RGB] +
+ SQUARES[((color >> 0) & 0xFF) - b + MAX_RGB]);
+ }
+
+ public String toString() {
+ StringBuffer buf = new StringBuffer();
+ if (parent == this) {
+ buf.append("root");
+ } else {
+ buf.append("node");
+ }
+ buf.append(' ');
+ buf.append(level);
+ buf.append(" [");
+ buf.append(mid_red);
+ buf.append(',');
+ buf.append(mid_green);
+ buf.append(',');
+ buf.append(mid_blue);
+ buf.append(']');
+ return new String(buf);
+ }
+ }
+ }
+}