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/*
 * Copyright 2007 ZXing authors
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package com.google.zxing.common.reedsolomon;

/**
 * 

Implements Reed-Solomon decoding, as the name implies.

* *

The algorithm will not be explained here, but the following references were helpful * in creating this implementation:

* * * *

Much credit is due to William Rucklidge since portions of this code are an indirect * port of his C++ Reed-Solomon implementation.

* * @author Sean Owen * @author William Rucklidge * @author sanfordsquires */ public final class ReedSolomonDecoder { private final GenericGF field; public ReedSolomonDecoder(GenericGF field) { this.field = field; } /** *

Decodes given set of received codewords, which include both data and error-correction * codewords. Really, this means it uses Reed-Solomon to detect and correct errors, in-place, * in the input.

* * @param received data and error-correction codewords * @param twoS number of error-correction codewords available * @throws ReedSolomonException if decoding fails for any reason */ public void decode(int[] received, int twoS) throws ReedSolomonException { GenericGFPoly poly = new GenericGFPoly(field, received); int[] syndromeCoefficients = new int[twoS]; boolean noError = true; for (int i = 0; i < twoS; i++) { int eval = poly.evaluateAt(field.exp(i + field.getGeneratorBase())); syndromeCoefficients[syndromeCoefficients.length - 1 - i] = eval; if (eval != 0) { noError = false; } } if (noError) { return; } GenericGFPoly syndrome = new GenericGFPoly(field, syndromeCoefficients); GenericGFPoly[] sigmaOmega = runEuclideanAlgorithm(field.buildMonomial(twoS, 1), syndrome, twoS); GenericGFPoly sigma = sigmaOmega[0]; GenericGFPoly omega = sigmaOmega[1]; int[] errorLocations = findErrorLocations(sigma); int[] errorMagnitudes = findErrorMagnitudes(omega, errorLocations); for (int i = 0; i < errorLocations.length; i++) { int position = received.length - 1 - field.log(errorLocations[i]); if (position < 0) { throw new ReedSolomonException("Bad error location"); } received[position] = GenericGF.addOrSubtract(received[position], errorMagnitudes[i]); } } private GenericGFPoly[] runEuclideanAlgorithm(GenericGFPoly a, GenericGFPoly b, int R) throws ReedSolomonException { // Assume a's degree is >= b's if (a.getDegree() < b.getDegree()) { GenericGFPoly temp = a; a = b; b = temp; } GenericGFPoly rLast = a; GenericGFPoly r = b; GenericGFPoly tLast = field.getZero(); GenericGFPoly t = field.getOne(); // Run Euclidean algorithm until r's degree is less than R/2 while (2 * r.getDegree() >= R) { GenericGFPoly rLastLast = rLast; GenericGFPoly tLastLast = tLast; rLast = r; tLast = t; // Divide rLastLast by rLast, with quotient in q and remainder in r if (rLast.isZero()) { // Oops, Euclidean algorithm already terminated? throw new ReedSolomonException("r_{i-1} was zero"); } r = rLastLast; GenericGFPoly q = field.getZero(); int denominatorLeadingTerm = rLast.getCoefficient(rLast.getDegree()); int dltInverse = field.inverse(denominatorLeadingTerm); while (r.getDegree() >= rLast.getDegree() && !r.isZero()) { int degreeDiff = r.getDegree() - rLast.getDegree(); int scale = field.multiply(r.getCoefficient(r.getDegree()), dltInverse); q = q.addOrSubtract(field.buildMonomial(degreeDiff, scale)); r = r.addOrSubtract(rLast.multiplyByMonomial(degreeDiff, scale)); } t = q.multiply(tLast).addOrSubtract(tLastLast); if (r.getDegree() >= rLast.getDegree()) { throw new IllegalStateException("Division algorithm failed to reduce polynomial? " + "r: " + r + ", rLast: " + rLast); } } int sigmaTildeAtZero = t.getCoefficient(0); if (sigmaTildeAtZero == 0) { throw new ReedSolomonException("sigmaTilde(0) was zero"); } int inverse = field.inverse(sigmaTildeAtZero); GenericGFPoly sigma = t.multiply(inverse); GenericGFPoly omega = r.multiply(inverse); return new GenericGFPoly[]{sigma, omega}; } private int[] findErrorLocations(GenericGFPoly errorLocator) throws ReedSolomonException { // This is a direct application of Chien's search int numErrors = errorLocator.getDegree(); if (numErrors == 1) { // shortcut return new int[] { errorLocator.getCoefficient(1) }; } int[] result = new int[numErrors]; int e = 0; for (int i = 1; i < field.getSize() && e < numErrors; i++) { if (errorLocator.evaluateAt(i) == 0) { result[e] = field.inverse(i); e++; } } if (e != numErrors) { throw new ReedSolomonException("Error locator degree does not match number of roots"); } return result; } private int[] findErrorMagnitudes(GenericGFPoly errorEvaluator, int[] errorLocations) { // This is directly applying Forney's Formula int s = errorLocations.length; int[] result = new int[s]; for (int i = 0; i < s; i++) { int xiInverse = field.inverse(errorLocations[i]); int denominator = 1; for (int j = 0; j < s; j++) { if (i != j) { //denominator = field.multiply(denominator, // GenericGF.addOrSubtract(1, field.multiply(errorLocations[j], xiInverse))); // Above should work but fails on some Apple and Linux JDKs due to a Hotspot bug. // Below is a funny-looking workaround from Steven Parkes int term = field.multiply(errorLocations[j], xiInverse); int termPlus1 = (term & 0x1) == 0 ? term | 1 : term & ~1; denominator = field.multiply(denominator, termPlus1); } } result[i] = field.multiply(errorEvaluator.evaluateAt(xiInverse), field.inverse(denominator)); if (field.getGeneratorBase() != 0) { result[i] = field.multiply(result[i], xiInverse); } } return result; } }




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