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/*
 * Copyright (c) 2011-2013, Peter Abeles. All Rights Reserved.
 *
 * This file is part of BoofCV (http://boofcv.org).
 *
 * 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 boofcv.alg.enhance;

import boofcv.alg.InputSanityCheck;
import boofcv.alg.enhance.impl.ImplEnhanceFilter;
import boofcv.alg.enhance.impl.ImplEnhanceHistogram;
import boofcv.alg.misc.ImageStatistics;
import boofcv.struct.image.*;

/**
 * 

* Operations for improving the visibility of images. *

* *

* See [1] for a discussion of algorithms found in this class. *

* *

* [1] R. C. Gonzalez, R. E. Woods, "Digitial Image Processing" 2nd Ed. 2002 *

* * @author Peter Abeles */ // TODO Add laplacian enhancement? public class EnhanceImageOps { /** * Computes a transformation table which will equalize the provided histogram. An equalized histogram spreads * the 'weight' across the whole spectrum of values. Often used to make dim images easier for people to see. * * @param histogram Input image histogram. * @param transform Output transformation table. */ public static void equalize( int histogram[] , int transform[] ) { int sum = 0; for( int i = 0; i < histogram.length; i++ ) { transform[i] = sum += histogram[i]; } int maxValue = histogram.length-1; for( int i = 0; i < histogram.length; i++ ) { transform[i] = (transform[i]*maxValue)/sum; } } /** * Applies the transformation table to the provided input image. * * @param input Input image. * @param transform Input transformation table. * @param output Output image. */ public static void applyTransform( ImageUInt8 input , int transform[] , ImageUInt8 output ) { InputSanityCheck.checkSameShape(input, output); ImplEnhanceHistogram.applyTransform(input,transform,output); } /** * Applies the transformation table to the provided input image. * * @param input Input image. * @param transform Input transformation table. * @param output Output image. */ public static void applyTransform( ImageUInt16 input , int transform[] , ImageUInt16 output ) { InputSanityCheck.checkSameShape(input, output); ImplEnhanceHistogram.applyTransform(input,transform,output); } /** * Applies the transformation table to the provided input image. * * @param input Input image. * @param minValue Minimum possible pixel value. * @param transform Input transformation table. * @param output Output image. */ public static void applyTransform( ImageSInt8 input , int transform[] , int minValue, ImageSInt8 output ) { InputSanityCheck.checkSameShape(input, output); ImplEnhanceHistogram.applyTransform(input,transform,minValue,output); } /** * Applies the transformation table to the provided input image. * * @param input Input image. * @param minValue Minimum possible pixel value. * @param transform Input transformation table. * @param output Output image. */ public static void applyTransform( ImageSInt16 input , int transform[] , int minValue, ImageSInt16 output ) { InputSanityCheck.checkSameShape(input, output); ImplEnhanceHistogram.applyTransform(input,transform,minValue,output); } /** * Applies the transformation table to the provided input image. * * @param input Input image. * @param minValue Minimum possible pixel value. * @param transform Input transformation table. * @param output Output image. */ public static void applyTransform( ImageSInt32 input , int transform[] , int minValue, ImageSInt32 output ) { InputSanityCheck.checkSameShape(input, output); ImplEnhanceHistogram.applyTransform(input,transform,minValue,output); } /** * Equalizes the local image histogram on a per pixel basis. * * @param input Input image. * @param radius Radius of square local histogram. * @param output Output image. * @param histogram Storage for image histogram. Must be large enough to contain all possible values. * @param transform Storage for transformation table. Must be large enough to contain all possible values. */ public static void equalizeLocal( ImageUInt8 input , int radius , ImageUInt8 output , int histogram[] , int transform[] ) { InputSanityCheck.checkSameShape(input, output); int width = radius*2+1; // use more efficient algorithms if possible if( input.width >= width && input.height >= width ) { ImplEnhanceHistogram.equalizeLocalInner(input,radius,output,histogram); // top border ImplEnhanceHistogram.equalizeLocalRow(input,radius,0,output,histogram,transform); // bottom border ImplEnhanceHistogram.equalizeLocalRow(input,radius,input.height-radius,output,histogram,transform); // left border ImplEnhanceHistogram.equalizeLocalCol(input,radius,0,output,histogram,transform); // right border ImplEnhanceHistogram.equalizeLocalCol(input,radius,input.width-radius,output,histogram,transform); } else if( input.width < width && input.height < width ) { // the local region is larger than the image. just use the full image algorithm ImageStatistics.histogram(input,histogram); equalize(histogram,transform); applyTransform(input,transform,output); } else { ImplEnhanceHistogram.equalizeLocalNaive(input,radius,output,transform); } } /** * Equalizes the local image histogram on a per pixel basis. * * @param input Input image. * @param radius Radius of square local histogram. * @param output Output image. * @param histogram Storage for image histogram. Must be large enough to contain all possible values. * @param transform Storage for transformation table. Must be large enough to contain all possible values. */ public static void equalizeLocal( ImageUInt16 input , int radius , ImageUInt16 output , int histogram[] , int transform[] ) { InputSanityCheck.checkSameShape(input, output); int width = radius*2+1; // use more efficient algorithms if possible if( input.width >= width && input.height >= width ) { ImplEnhanceHistogram.equalizeLocalInner(input,radius,output,histogram); // top border ImplEnhanceHistogram.equalizeLocalRow(input,radius,0,output,histogram,transform); // bottom border ImplEnhanceHistogram.equalizeLocalRow(input,radius,input.height-radius,output,histogram,transform); // left border ImplEnhanceHistogram.equalizeLocalCol(input,radius,0,output,histogram,transform); // right border ImplEnhanceHistogram.equalizeLocalCol(input,radius,input.width-radius,output,histogram,transform); } else if( input.width < width && input.height < width ) { // the local region is larger than the image. just use the full image algorithm ImageStatistics.histogram(input,histogram); equalize(histogram,transform); applyTransform(input,transform,output); } else { ImplEnhanceHistogram.equalizeLocalNaive(input,radius,output,transform); } } /** * Applies a Laplacian-4 based sharpen filter to the image. * * @param input Input image. * @param output Output image. */ public static void sharpen4( ImageUInt8 input , ImageUInt8 output ) { InputSanityCheck.checkSameShape(input, output); ImplEnhanceFilter.sharpenInner4(input,output,0,255); ImplEnhanceFilter.sharpenBorder4(input,output,0,255); } /** * Applies a Laplacian-4 based sharpen filter to the image. * * @param input Input image. * @param output Output image. */ public static void sharpen4( ImageFloat32 input , ImageFloat32 output ) { InputSanityCheck.checkSameShape(input, output); ImplEnhanceFilter.sharpenInner4(input,output,0,255); ImplEnhanceFilter.sharpenBorder4(input, output, 0, 255); } /** * Applies a Laplacian-8 based sharpen filter to the image. * * @param input Input image. * @param output Output image. */ public static void sharpen8( ImageUInt8 input , ImageUInt8 output ) { InputSanityCheck.checkSameShape(input, output); ImplEnhanceFilter.sharpenInner8(input,output,0,255); ImplEnhanceFilter.sharpenBorder8(input, output, 0, 255); } /** * Applies a Laplacian-8 based sharpen filter to the image. * * @param input Input image. * @param output Output image. */ public static void sharpen8( ImageFloat32 input , ImageFloat32 output ) { InputSanityCheck.checkSameShape(input, output); ImplEnhanceFilter.sharpenInner8(input,output,0,255); ImplEnhanceFilter.sharpenBorder8(input, output, 0, 255); } }




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