boofcv.alg.enhance.EnhanceImageOps Maven / Gradle / Ivy
/*
* 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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