demo场景：
将2张静态的png格式图片组合生成一个gif图片，间隔500毫秒，关键类：AnimatedGifEncoder
如需要解析gif获取每帧的图片，可参考上一篇博客：《android 开发 解码gif图片，获取每帧bitmap》
使用方法：
/** * 生成gif图片 */ void makeGif() { String path = Environment.getExternalStorageDirectory().getAbsolutePath() +"/data/data/"+ this.getPackageName()+"/cache"; Bitmap bmp1 = BitmapFactory.decodeResource(getResources(), R.drawable.gif10); //png格式资源图片 Bitmap bmp2 = BitmapFactory.decodeResource(getResources(), R.drawable.gif13);//png格式资源图片 File pathFile = new File(path); File gifFile = new File(pathFile,"add_1.gif"); if(!pathFile.exists()) pathFile.mkdirs(); if(!gifFile.exists()) try { gifFile.createNewFile(); } catch (IOException e1) { // TODO Auto-generated catch block e1.printStackTrace(); } OutputStream os; try { os = new FileOutputStream(gifFile); gifEncoder.start(os); //注意顺序 gifEncoder.addFrame(bmp1); gifEncoder.addFrame(bmp2); gifEncoder.setDelay(500); gifEncoder.setRepeat(0); gifEncoder.finish(); } catch (FileNotFoundException e) { // TODO Auto-generated catch block e.printStackTrace(); } }
关键的编码gif代码：
import java.io.IOException; import java.io.OutputStream; import android.graphics.Bitmap; import android.graphics.Bitmap.Config; import android.graphics.Canvas; import android.graphics.Paint; public class AnimatedGifEncoder { protected int width; // image size protected int height; protected int x = 0; protected int y = 0; protected int transparent = -1; // transparent color if given protected int transIndex; // transparent index in color table protected int repeat = -1; // no repeat protected int delay = 0; // frame delay (hundredths) protected boolean started = false; // ready to output frames protected OutputStream out; protected Bitmap image; // current frame protected byte[] pixels; // BGR byte array from frame protected byte[] indexedPixels; // converted frame indexed to palette protected int colorDepth; // number of bit planes protected byte[] colorTab; // RGB palette protected boolean[] usedEntry = new boolean[256]; // active palette entries protected int palSize = 7; // color table size (bits-1) protected int dispose = -1; // disposal code (-1 = use default) protected boolean closeStream = false; // close stream when finished protected boolean firstFrame = true; protected boolean sizeSet = false; // if false, get size from first frame protected int sample = 10; // default sample interval for quantizer /** * Sets the delay time between each frame, or changes it for subsequent frames * (applies to last frame added). * * @param ms * int delay time in milliseconds */ public void setDelay(int ms) { delay = ms / 10; } /** * Sets the GIF frame disposal code for the last added frame and any * subsequent frames. Default is 0 if no transparent color has been set, * otherwise 2. * * @param code * int disposal code. */ public void setDispose(int code) { if (code >= 0) { dispose = code; } } /** * Sets the number of times the set of GIF frames should be played. Default is * 1; 0 means play indefinitely. Must be invoked before the first image is * added. * * @param iter * int number of iterations. * @return */ public void setRepeat(int iter) { if (iter >= 0) { repeat = iter; } } /** * Sets the transparent color for the last added frame and any subsequent * frames. Since all colors are subject to modification in the quantization * process, the color in the final palette for each frame closest to the given * color becomes the transparent color for that frame. May be set to null to * indicate no transparent color. * * @param c * Color to be treated as transparent on display. */ public void setTransparent(int c) { transparent = c; } /** * Adds next GIF frame. The frame is not written immediately, but is actually * deferred until the next frame is received so that timing data can be * inserted. Invoking <code>finish()</code> flushes all frames. If * <code>setSize</code> was not invoked, the size of the first image is used * for all subsequent frames. * * @param im * BufferedImage containing frame to write. * @return true if successful. */ public boolean addFrame(Bitmap im) { if ((im == null) || !started) { return false; } boolean ok = true; try { if (!sizeSet) { // use first frame's size setSize(im.getWidth(), im.getHeight()); } image = im; getImagePixels(); // convert to correct format if necessary analyzePixels(); // build color table & map pixels if (firstFrame) { writeLSD(); // logical screen descriptior writePalette(); // global color table if (repeat >= 0) { // use NS app extension to indicate reps writeNetscapeExt(); } } writeGraphicCtrlExt(); // write graphic control extension writeImageDesc(); // image descriptor if (!firstFrame) { writePalette(); // local color table } writePixels(); // encode and write pixel data firstFrame = false; } catch (IOException e) { ok = false; } return ok; } /** * Flushes any pending data and closes output file. If writing to an * OutputStream, the stream is not closed. */ public boolean finish() { if (!started) return false; boolean ok = true; started = false; try { out.write(0x3b); // gif trailer out.flush(); if (closeStream) { out.close(); } } catch (IOException e) { ok = false; } // reset for subsequent use transIndex = 0; out = null; image = null; pixels = null; indexedPixels = null; colorTab = null; closeStream = false; firstFrame = true; return ok; } /** * Sets frame rate in frames per second. Equivalent to * <code>setDelay(1000/fps)</code>. * * @param fps * float frame rate (frames per second) */ public void setFrameRate(float fps) { if (fps != 0f) { delay = (int)(100 / fps); } } /** * Sets quality of color quantization (conversion of images to the maximum 256 * colors allowed by the GIF specification). Lower values (minimum = 1) * produce better colors, but slow processing significantly. 10 is the * default, and produces good color mapping at reasonable speeds. Values * greater than 20 do not yield significant improvements in speed. * * @param quality * int greater than 0. * @return */ public void setQuality(int quality) { if (quality < 1) quality = 1; sample = quality; } /** * Sets the GIF frame size. The default size is the size of the first frame * added if this method is not invoked. * * @param w * int frame width. * @param h * int frame width. */ public void setSize(int w, int h) { width = w; height = h; if (width < 1) width = 320; if (height < 1) height = 240; sizeSet = true; } /** * Sets the GIF frame position. The position is 0,0 by default. * Useful for only updating a section of the image * * @param w * int frame width. * @param h * int frame width. */ public void setPosition(int x, int y) { this.x = x; this.y = y; } /** * Initiates GIF file creation on the given stream. The stream is not closed * automatically. * * @param os * OutputStream on which GIF images are written. * @return false if initial write failed. */ public boolean start(OutputStream os) { if (os == null) return false; boolean ok = true; closeStream = false; out = os; try { writeString("GIF89a"); // header } catch (IOException e) { ok = false; } return started = ok; } /** * Analyzes image colors and creates color map. */ protected void analyzePixels() { int len = pixels.length; int nPix = len / 3; indexedPixels = new byte[nPix]; NeuQuant nq = new NeuQuant(pixels, len, sample); // initialize quantizer colorTab = nq.process(); // create reduced palette // convert map from BGR to RGB for (int i = 0; i < colorTab.length; i += 3) { byte temp = colorTab[i]; colorTab[i] = colorTab[i + 2]; colorTab[i + 2] = temp; usedEntry[i / 3] = false; } // map image pixels to new palette int k = 0; for (int i = 0; i < nPix; i++) { int index = nq.map(pixels[k++] & 0xff, pixels[k++] & 0xff, pixels[k++] & 0xff); usedEntry[index] = true; indexedPixels[i] = (byte) index; } pixels = null; colorDepth = 8; palSize = 7; // get closest match to transparent color if specified if (transparent != -1) { transIndex = findClosest(transparent); } } /** * Returns index of palette color closest to c * */ protected int findClosest(int c) { if (colorTab == null) return -1; int r = (c >> 16) & 0xff; int g = (c >> 8) & 0xff; int b = (c >> 0) & 0xff; int minpos = 0; int dmin = 256 * 256 * 256; int len = colorTab.length; for (int i = 0; i < len;) { int dr = r - (colorTab[i++] & 0xff); int dg = g - (colorTab[i++] & 0xff); int db = b - (colorTab[i] & 0xff); int d = dr * dr + dg * dg + db * db; int index = i / 3; if (usedEntry[index] && (d < dmin)) { dmin = d; minpos = index; } i++; } return minpos; } /** * Extracts image pixels into byte array "pixels" */ protected void getImagePixels() { int w = image.getWidth(); int h = image.getHeight(); if ((w != width) || (h != height)) { // create new image with right size/format Bitmap temp = Bitmap.createBitmap(width, height, Config.RGB_565); Canvas g = new Canvas(temp); g.drawBitmap(image, 0, 0, new Paint()); image = temp; } int[] data = getImageData(image); pixels = new byte[data.length * 3]; for (int i = 0; i < data.length; i++) { int td = data[i]; int tind = i * 3; pixels[tind++] = (byte) ((td >> 0) & 0xFF); pixels[tind++] = (byte) ((td >> 8) & 0xFF); pixels[tind] = (byte) ((td >> 16) & 0xFF); } } protected int[] getImageData(Bitmap img) { int w = img.getWidth(); int h = img.getHeight(); int[] data = new int[w * h]; img.getPixels(data, 0, w, 0, 0, w, h); return data; } /** * Writes Graphic Control Extension */ protected void writeGraphicCtrlExt() throws IOException { out.write(0x21); // extension introducer out.write(0xf9); // GCE label out.write(4); // data block size int transp, disp; if (transparent == -1) { transp = 0; disp = 0; // dispose = no action } else { transp = 1; disp = 2; // force clear if using transparent color } if (dispose >= 0) { disp = dispose & 7; // user override } disp <<= 2; // packed fields out.write(0 | // 1:3 reserved disp | // 4:6 disposal 0 | // 7 user input - 0 = none transp); // 8 transparency flag writeShort(delay); // delay x 1/100 sec out.write(transIndex); // transparent color index out.write(0); // block terminator } /** * Writes Image Descriptor */ protected void writeImageDesc() throws IOException { out.write(0x2c); // image separator writeShort(x); // image position x,y = 0,0 writeShort(y); writeShort(width); // image size writeShort(height); // packed fields if (firstFrame) { // no LCT - GCT is used for first (or only) frame out.write(0); } else { // specify normal LCT out.write(0x80 | // 1 local color table 1=yes 0 | // 2 interlace - 0=no 0 | // 3 sorted - 0=no 0 | // 4-5 reserved palSize); // 6-8 size of color table } } /** * Writes Logical Screen Descriptor */ protected void writeLSD() throws IOException { // logical screen size writeShort(width); writeShort(height); // packed fields out.write((0x80 | // 1 : global color table flag = 1 (gct used) 0x70 | // 2-4 : color resolution = 7 0x00 | // 5 : gct sort flag = 0 palSize)); // 6-8 : gct size out.write(0); // background color index out.write(0); // pixel aspect ratio - assume 1:1 } /** * Writes Netscape application extension to define repeat count. */ protected void writeNetscapeExt() throws IOException { out.write(0x21); // extension introducer out.write(0xff); // app extension label out.write(11); // block size writeString("NETSCAPE" + "2.0"); // app id + auth code out.write(3); // sub-block size out.write(1); // loop sub-block id writeShort(repeat); // loop count (extra iterations, 0=repeat forever) out.write(0); // block terminator } /** * Writes color table */ protected void writePalette() throws IOException { out.write(colorTab, 0, colorTab.length); int n = (3 * 256) - colorTab.length; for (int i = 0; i < n; i++) { out.write(0); } } /** * Encodes and writes pixel data */ protected void writePixels() throws IOException { LZWEncoder encoder = new LZWEncoder(width, height, indexedPixels, colorDepth); encoder.encode(out); } /** * Write 16-bit value to output stream, LSB first */ protected void writeShort(int value) throws IOException { out.write(value & 0xff); out.write((value >> 8) & 0xff); } /** * Writes string to output stream */ protected void writeString(String s) throws IOException { for (int i = 0; i < s.length(); i++) { out.write((byte) s.charAt(i)); } } } /* * 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 class NeuQuant { protected static final int netsize = 256; /* number of colours used */ /* four primes near 500 - assume no image has a length so large */ /* that it is divisible by all four primes */ protected static final int prime1 = 499; protected static final int prime2 = 491; protected static final int prime3 = 487; protected static final int prime4 = 503; protected static final int minpicturebytes = (3 * prime4); /* minimum size for input image */ /* * 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) */ /* * Network Definitions ------------------- */ protected static final int maxnetpos = (netsize - 1); protected static final int netbiasshift = 4; /* bias for colour values */ protected static final int ncycles = 100; /* no. of learning cycles */ /* defs for freq and bias */ protected static final int intbiasshift = 16; /* bias for fractions */ protected static final int intbias = (((int) 1) << intbiasshift); protected static final int gammashift = 10; /* gamma = 1024 */ protected static final int gamma = (((int) 1) << gammashift); protected static final int betashift = 10; protected static final int beta = (intbias >> betashift); /* beta = 1/1024 */ protected static final int betagamma = (intbias << (gammashift - betashift)); /* defs for decreasing radius factor */ protected static final int initrad = (netsize >> 3); /* * for 256 cols, radius * starts */ protected static final int radiusbiasshift = 6; /* at 32.0 biased by 6 bits */ protected static final int radiusbias = (((int) 1) << radiusbiasshift); protected static final int initradius = (initrad * radiusbias); /* * and * decreases * by a */ protected static final int radiusdec = 30; /* factor of 1/30 each cycle */ /* defs for decreasing alpha factor */ protected static final int alphabiasshift = 10; /* alpha starts at 1.0 */ protected static final int initalpha = (((int) 1) << alphabiasshift); protected int alphadec; /* biased by 10 bits */ /* radbias and alpharadbias used for radpower calculation */ protected static final int radbiasshift = 8; protected static final int radbias = (((int) 1) << radbiasshift); protected static final int alpharadbshift = (alphabiasshift + radbiasshift); protected static final int alpharadbias = (((int) 1) << alpharadbshift); /* * Types and Global Variables -------------------------- */ protected byte[] thepicture; /* the input image itself */ protected int lengthcount; /* lengthcount = H*W*3 */ protected int samplefac; /* sampling factor 1..30 */ // typedef int pixel[4]; /* BGRc */ protected int[][] network; /* the network itself - [netsize][4] */ protected int[] netindex = new int[256]; /* for network lookup - really 256 */ protected int[] bias = new int[netsize]; /* bias and freq arrays for learning */ protected int[] freq = new int[netsize]; protected int[] radpower = new int[initrad]; /* radpower for precomputation */ /* * Initialise network in range (0,0,0) to (255,255,255) and set parameters * ----------------------------------------------------------------------- */ public NeuQuant(byte[] thepic, int len, int sample) { int i; int[] p; thepicture = thepic; lengthcount = len; samplefac = sample; network = new int[netsize][]; for (i = 0; i < netsize; i++) { network[i] = new int[4]; p = network[i]; p[0] = p[1] = p[2] = (i << (netbiasshift + 8)) / netsize; freq[i] = intbias / netsize; /* 1/netsize */ bias[i] = 0; } } public byte[] colorMap() { byte[] map = new byte[3 * netsize]; int[] index = new int[netsize]; for (int i = 0; i < netsize; i++) index[network[i][3]] = i; int k = 0; for (int i = 0; i < netsize; i++) { int j = index[i]; map[k++] = (byte) (network[j][0]); map[k++] = (byte) (network[j][1]); map[k++] = (byte) (network[j][2]); } return map; } /* * Insertion sort of network and building of netindex[0..255] (to do after * unbias) * ------------------------------------------------------------------------------- */ public void inxbuild() { int i, j, smallpos, smallval; int[] p; int[] q; int previouscol, startpos; previouscol = 0; startpos = 0; for (i = 0; i < netsize; i++) { p = network[i]; smallpos = i; smallval = p[1]; /* index on g */ /* find smallest in i..netsize-1 */ for (j = i + 1; j < netsize; j++) { q = network[j]; if (q[1] < smallval) { /* index on g */ smallpos = j; smallval = q[1]; /* index on g */ } } q = network[smallpos]; /* swap p (i) and q (smallpos) entries */ if (i != smallpos) { j = q[0]; q[0] = p[0]; p[0] = j; j = q[1]; q[1] = p[1]; p[1] = j; j = q[2]; q[2] = p[2]; p[2] = j; j = q[3]; q[3] = p[3]; p[3] = j; } /* smallval entry is now in position i */ if (smallval != previouscol) { netindex[previouscol] = (startpos + i) >> 1; for (j = previouscol + 1; j < smallval; j++) netindex[j] = i; previouscol = smallval; startpos = i; } } netindex[previouscol] = (startpos + maxnetpos) >> 1; for (j = previouscol + 1; j < 256; j++) netindex[j] = maxnetpos; /* really 256 */ } /* * Main Learning Loop ------------------ */ public void learn() { int i, j, b, g, r; int radius, rad, alpha, step, delta, samplepixels; byte[] p; int pix, lim; if (lengthcount < minpicturebytes) samplefac = 1; alphadec = 30 + ((samplefac - 1) / 3); p = thepicture; pix = 0; lim = lengthcount; samplepixels = lengthcount / (3 * samplefac); delta = samplepixels / ncycles; alpha = initalpha; radius = initradius; rad = radius >> radiusbiasshift; if (rad <= 1) rad = 0; for (i = 0; i < rad; i++) radpower[i] = alpha * (((rad * rad - i * i) * radbias) / (rad * rad)); // fprintf(stderr,"beginning 1D learning: initial radius=%d ", rad); if (lengthcount < minpicturebytes) step = 3; else if ((lengthcount % prime1) != 0) step = 3 * prime1; else { if ((lengthcount % prime2) != 0) step = 3 * prime2; else { if ((lengthcount % prime3) != 0) step = 3 * prime3; else step = 3 * prime4; } } i = 0; while (i < samplepixels) { b = (p[pix + 0] & 0xff) << netbiasshift; g = (p[pix + 1] & 0xff) << netbiasshift; r = (p[pix + 2] & 0xff) << netbiasshift; j = contest(b, g, r); altersingle(alpha, j, b, g, r); if (rad != 0) alterneigh(rad, j, b, g, r); /* alter neighbours */ pix += step; if (pix >= lim) pix -= lengthcount; i++; if (delta == 0) delta = 1; if (i % delta == 0) { alpha -= alpha / alphadec; radius -= radius / radiusdec; rad = radius >> radiusbiasshift; if (rad <= 1) rad = 0; for (j = 0; j < rad; j++) radpower[j] = alpha * (((rad * rad - j * j) * radbias) / (rad * rad)); } } // fprintf(stderr,"finished 1D learning: final alpha=%f // ! ",((float)alpha)/initalpha); } /* * Search for BGR values 0..255 (after net is unbiased) and return colour * index * ---------------------------------------------------------------------------- */ public int map(int b, int g, int r) { int i, j, dist, a, bestd; int[] p; int best; bestd = 1000; /* biggest possible dist is 256*3 */ best = -1; i = netindex[g]; /* index on g */ j = i - 1; /* start at netindex[g] and work outwards */ while ((i < netsize) || (j >= 0)) { if (i < netsize) { p = network[i]; dist = p[1] - g; /* inx key */ if (dist >= bestd) i = netsize; /* stop iter */ else { i++; if (dist < 0) dist = -dist; a = p[0] - b; if (a < 0) a = -a; dist += a; if (dist < bestd) { a = p[2] - r; if (a < 0) a = -a; dist += a; if (dist < bestd) { bestd = dist; best = p[3]; } } } } if (j >= 0) { p = network[j]; dist = g - p[1]; /* inx key - reverse dif */ if (dist >= bestd) j = -1; /* stop iter */ else { j--; if (dist < 0) dist = -dist; a = p[0] - b; if (a < 0) a = -a; dist += a; if (dist < bestd) { a = p[2] - r; if (a < 0) a = -a; dist += a; if (dist < bestd) { bestd = dist; best = p[3]; } } } } } return (best); } public byte[] process() { learn(); unbiasnet(); inxbuild(); return colorMap(); } /* * Unbias network to give byte values 0..255 and record position i to prepare * for sort * ----------------------------------------------------------------------------------- */ public void unbiasnet() { int i; for (i = 0; i < netsize; i++) { network[i][0] >>= netbiasshift; network[i][1] >>= netbiasshift; network[i][2] >>= netbiasshift; network[i][3] = i; /* record colour no */ } } /* * Move adjacent neurons by precomputed alpha*(1-((i-j)^2/[r]^2)) in * radpower[|i-j|] * --------------------------------------------------------------------------------- */ protected void alterneigh(int rad, int i, int b, int g, int r) { int j, k, lo, hi, a, m; int[] p; lo = i - rad; if (lo < -1) lo = -1; hi = i + rad; if (hi > netsize) hi = netsize; j = i + 1; k = i - 1; m = 1; while ((j < hi) || (k > lo)) { a = radpower[m++]; if (j < hi) { p = network[j++]; try { p[0] -= (a * (p[0] - b)) / alpharadbias; p[1] -= (a * (p[1] - g)) / alpharadbias; p[2] -= (a * (p[2] - r)) / alpharadbias; } catch (Exception e) { } // prevents 1.3 miscompilation } if (k > lo) { p = network[k--]; try { p[0] -= (a * (p[0] - b)) / alpharadbias; p[1] -= (a * (p[1] - g)) / alpharadbias; p[2] -= (a * (p[2] - r)) / alpharadbias; } catch (Exception e) { } } } } /* * Move neuron i towards biased (b,g,r) by factor alpha * ---------------------------------------------------- */ protected void altersingle(int alpha, int i, int b, int g, int r) { /* alter hit neuron */ int[] n = network[i]; n[0] -= (alpha * (n[0] - b)) / initalpha; n[1] -= (alpha * (n[1] - g)) / initalpha; n[2] -= (alpha * (n[2] - r)) / initalpha; } /* * Search for biased BGR values ---------------------------- */ protected int contest(int b, int g, int r) { /* finds closest neuron (min dist) and updates freq */ /* finds best neuron (min dist-bias) and returns position */ /* for frequently chosen neurons, freq[i] is high and bias[i] is negative */ /* bias[i] = gamma*((1/netsize)-freq[i]) */ int i, dist, a, biasdist, betafreq; int bestpos, bestbiaspos, bestd, bestbiasd; int[] n; bestd = ~(((int) 1) << 31); bestbiasd = bestd; bestpos = -1; bestbiaspos = bestpos; for (i = 0; i < netsize; i++) { n = network[i]; dist = n[0] - b; if (dist < 0) dist = -dist; a = n[1] - g; if (a < 0) a = -a; dist += a; a = n[2] - r; if (a < 0) a = -a; dist += a; if (dist < bestd) { bestd = dist; bestpos = i; } biasdist = dist - ((bias[i]) >> (intbiasshift - netbiasshift)); if (biasdist < bestbiasd) { bestbiasd = biasdist; bestbiaspos = i; } betafreq = (freq[i] >> betashift); freq[i] -= betafreq; bias[i] += (betafreq << gammashift); } freq[bestpos] += beta; bias[bestpos] -= betagamma; return (bestbiaspos); } } // ============================================================================== // Adapted from Jef Poskanzer's Java port by way of J. M. G. Elliott. // K Weiner 12/00 class LZWEncoder { private static final int EOF = -1; private int imgW, imgH; private byte[] pixAry; private int initCodeSize; private int remaining; private int curPixel; // GIFCOMPR.C - GIF Image compression routines // // Lempel-Ziv compression based on 'compress'. GIF modifications by // David Rowley (mgardi@watdcsu.waterloo.edu) // General DEFINEs static final int BITS = 12; static final int HSIZE = 5003; // 80% occupancy // GIF Image compression - modified 'compress' // // Based on: compress.c - File compression ala IEEE Computer, June 1984. // // By Authors: Spencer W. Thomas (decvax!harpo!utah-cs!utah-gr!thomas) // Jim McKie (decvax!mcvax!jim) // Steve Davies (decvax!vax135!petsd!peora!srd) // Ken Turkowski (decvax!decwrl!turtlevax!ken) // James A. Woods (decvax!ihnp4!ames!jaw) // Joe Orost (decvax!vax135!petsd!joe) int n_bits; // number of bits/code int maxbits = BITS; // user settable max # bits/code int maxcode; // maximum code, given n_bits int maxmaxcode = 1 << BITS; // should NEVER generate this code int[] htab = new int[HSIZE]; int[] codetab = new int[HSIZE]; int hsize = HSIZE; // for dynamic table sizing int free_ent = 0; // first unused entry // block compression parameters -- after all codes are used up, // and compression rate changes, start over. boolean clear_flg = false; // Algorithm: use open addressing double hashing (no chaining) on the // prefix code / next character combination. We do a variant of Knuth's // algorithm D (vol. 3, sec. 6.4) along with G. Knott's relatively-prime // secondary probe. Here, the modular division first probe is gives way // to a faster exclusive-or manipulation. Also do block compression with // an adaptive reset, whereby the code table is cleared when the compression // ratio decreases, but after the table fills. The variable-length output // codes are re-sized at this point, and a special CLEAR code is generated // for the decompressor. Late addition: construct the table according to // file size for noticeable speed improvement on small files. Please direct // questions about this implementation to ames!jaw. int g_init_bits; int ClearCode; int EOFCode; // output // // Output the given code. // Inputs: // code: A n_bits-bit integer. If == -1, then EOF. This assumes // that n_bits =< wordsize - 1. // Outputs: // Outputs code to the file. // Assumptions: // Chars are 8 bits long. // Algorithm: // Maintain a BITS character long buffer (so that 8 codes will // fit in it exactly). Use the VAX insv instruction to insert each // code in turn. When the buffer fills up empty it and start over. int cur_accum = 0; int cur_bits = 0; int masks[] = { 0x0000, 0x0001, 0x0003, 0x0007, 0x000F, 0x001F, 0x003F, 0x007F, 0x00FF, 0x01FF, 0x03FF, 0x07FF, 0x0FFF, 0x1FFF, 0x3FFF, 0x7FFF, 0xFFFF }; // Number of characters so far in this 'packet' int a_count; // Define the storage for the packet accumulator byte[] accum = new byte[256]; // ---------------------------------------------------------------------------- LZWEncoder(int width, int height, byte[] pixels, int color_depth) { imgW = width; imgH = height; pixAry = pixels; initCodeSize = Math.max(2, color_depth); } // Add a character to the end of the current packet, and if it is 254 // characters, flush the packet to disk. void char_out(byte c, OutputStream outs) throws IOException { accum[a_count++] = c; if (a_count >= 254) flush_char(outs); } // Clear out the hash table // table clear for block compress void cl_block(OutputStream outs) throws IOException { cl_hash(hsize); free_ent = ClearCode + 2; clear_flg = true; output(ClearCode, outs); } // reset code table void cl_hash(int hsize) { for (int i = 0; i < hsize; ++i) htab[i] = -1; } void compress(int init_bits, OutputStream outs) throws IOException { int fcode; int i /* = 0 */; int c; int ent; int disp; int hsize_reg; int hshift; // Set up the globals: g_init_bits - initial number of bits g_init_bits = init_bits; // Set up the necessary values clear_flg = false; n_bits = g_init_bits; maxcode = MAXCODE(n_bits); ClearCode = 1 << (init_bits - 1); EOFCode = ClearCode + 1; free_ent = ClearCode + 2; a_count = 0; // clear packet ent = nextPixel(); hshift = 0; for (fcode = hsize; fcode < 65536; fcode *= 2) ++hshift; hshift = 8 - hshift; // set hash code range bound hsize_reg = hsize; cl_hash(hsize_reg); // clear hash table output(ClearCode, outs); outer_loop: while ((c = nextPixel()) != EOF) { fcode = (c << maxbits) + ent; i = (c << hshift) ^ ent; // xor hashing if (htab[i] == fcode) { ent = codetab[i]; continue; } else if (htab[i] >= 0) // non-empty slot { disp = hsize_reg - i; // secondary hash (after G. Knott) if (i == 0) disp = 1; do { if ((i -= disp) < 0) i += hsize_reg; if (htab[i] == fcode) { ent = codetab[i]; continue outer_loop; } } while (htab[i] >= 0); } output(ent, outs); ent = c; if (free_ent < maxmaxcode) { codetab[i] = free_ent++; // code -> hashtable htab[i] = fcode; } else cl_block(outs); } // Put out the final code. output(ent, outs); output(EOFCode, outs); } // ---------------------------------------------------------------------------- void encode(OutputStream os) throws IOException { os.write(initCodeSize); // write "initial code size" byte remaining = imgW * imgH; // reset navigation variables curPixel = 0; compress(initCodeSize + 1, os); // compress and write the pixel data os.write(0); // write block terminator } // Flush the packet to disk, and reset the accumulator void flush_char(OutputStream outs) throws IOException { if (a_count > 0) { outs.write(a_count); outs.write(accum, 0, a_count); a_count = 0; } } final int MAXCODE(int n_bits) { return (1 << n_bits) - 1; } // ---------------------------------------------------------------------------- // Return the next pixel from the image // ---------------------------------------------------------------------------- private int nextPixel() { if (remaining == 0) return EOF; --remaining; byte pix = pixAry[curPixel++]; return pix & 0xff; } void output(int code, OutputStream outs) throws IOException { cur_accum &= masks[cur_bits]; if (cur_bits > 0) cur_accum |= (code << cur_bits); else cur_accum = code; cur_bits += n_bits; while (cur_bits >= 8) { char_out((byte) (cur_accum & 0xff), outs); cur_accum >>= 8; cur_bits -= 8; } // If the next entry is going to be too big for the code size, // then increase it, if possible. if (free_ent > maxcode || clear_flg) { if (clear_flg) { maxcode = MAXCODE(n_bits = g_init_bits); clear_flg = false; } else { ++n_bits; if (n_bits == maxbits) maxcode = maxmaxcode; else maxcode = MAXCODE(n_bits); } } if (code == EOFCode) { // At EOF, write the rest of the buffer. while (cur_bits > 0) { char_out((byte) (cur_accum & 0xff), outs); cur_accum >>= 8; cur_bits -= 8; } flush_char(outs); } } }