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/*
* Copyright (c) 2011-2016, 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.filter.blur;
import boofcv.alg.InputSanityCheck;
import boofcv.alg.filter.blur.impl.ImplMedianHistogramInner;
import boofcv.alg.filter.blur.impl.ImplMedianSortEdgeNaive;
import boofcv.alg.filter.blur.impl.ImplMedianSortNaive;
import boofcv.alg.filter.convolve.ConvolveImageMean;
import boofcv.alg.filter.convolve.ConvolveNormalized;
import boofcv.core.image.GeneralizedImageOps;
import boofcv.factory.filter.kernel.FactoryKernelGaussian;
import boofcv.struct.convolve.Kernel1D_F32;
import boofcv.struct.convolve.Kernel1D_F64;
import boofcv.struct.convolve.Kernel1D_I32;
import boofcv.struct.image.*;
/**
* Catch all class for function which "blur" an image, typically used to "reduce" the amount
* of noise in the image.
*
* @author Peter Abeles
*/
public class BlurImageOps {
/**
* Applies a mean box filter.
*
* @param input Input image. Not modified.
* @param output (Optional) Storage for output image, Can be null. Modified.
* @param radius Radius of the box blur function.
* @param storage (Optional) Storage for intermediate results. Same size as input image. Can be null.
* @return Output blurred image.
*/
public static GrayU8 mean(GrayU8 input, GrayU8 output, int radius, GrayU8 storage) {
if( radius <= 0 )
throw new IllegalArgumentException("Radius must be > 0");
output = InputSanityCheck.checkDeclare(input,output);
storage = InputSanityCheck.checkDeclare(input,storage);
ConvolveImageMean.horizontal(input,storage,radius);
ConvolveImageMean.vertical(storage, output, radius);
return output;
}
/**
* Applies a median filter.
*
* @param input Input image. Not modified.
* @param output (Optional) Storage for output image, Can be null. Modified.
* @param radius Radius of the median blur function.
* @return Output blurred image.
*/
public static GrayU8 median(GrayU8 input, GrayU8 output, int radius) {
if( radius <= 0 )
throw new IllegalArgumentException("Radius must be > 0");
output = InputSanityCheck.checkDeclare(input,output);
int w = radius*2+1;
int offset[] = new int[ w*w ];
int histogram[] = new int[ 256 ];
ImplMedianHistogramInner.process(input, output, radius, offset, histogram);
ImplMedianSortEdgeNaive.process(input, output, radius, offset);
return output;
}
/**
* Applies Gaussian blur.
*
* @param input Input image. Not modified.
* @param output (Optional) Storage for output image, Can be null. Modified.
* @param sigma Gaussian distribution's sigma. If ≤ 0 then will be selected based on radius.
* @param radius Radius of the Gaussian blur function. If ≤ 0 then radius will be determined by sigma.
* @param storage (Optional) Storage for intermediate results. Same size as input image. Can be null.
* @return Output blurred image.
*/
public static GrayU8 gaussian(GrayU8 input, GrayU8 output, double sigma , int radius,
GrayU8 storage ) {
output = InputSanityCheck.checkDeclare(input,output);
storage = InputSanityCheck.checkDeclare(input,storage,GrayU8.class);
Kernel1D_I32 kernel = FactoryKernelGaussian.gaussian(Kernel1D_I32.class,sigma,radius);
ConvolveNormalized.horizontal(kernel, input, storage);
ConvolveNormalized.vertical(kernel,storage,output);
return output;
}
/**
* Applies a mean box filter.
*
* @param input Input image. Not modified.
* @param output (Optional) Storage for output image, Can be null. Modified.
* @param radius Radius of the box blur function.
* @param storage (Optional) Storage for intermediate results. Same size as input image. Can be null.
* @return Output blurred image.
*/
public static GrayF32 mean(GrayF32 input, GrayF32 output, int radius, GrayF32 storage) {
if( radius <= 0 )
throw new IllegalArgumentException("Radius must be > 0");
output = InputSanityCheck.checkDeclare(input,output);
storage = InputSanityCheck.checkDeclare(input,storage);
ConvolveImageMean.horizontal(input,storage,radius);
ConvolveImageMean.vertical(storage,output,radius);
return output;
}
/**
* Applies a mean box filter.
*
* @param input Input image. Not modified.
* @param output (Optional) Storage for output image, Can be null. Modified.
* @param radius Radius of the box blur function.
* @param storage (Optional) Storage for intermediate results. Same size as input image. Can be null.
* @return Output blurred image.
*/
public static GrayF64 mean(GrayF64 input, GrayF64 output, int radius, GrayF64 storage) {
if( radius <= 0 )
throw new IllegalArgumentException("Radius must be > 0");
output = InputSanityCheck.checkDeclare(input,output);
storage = InputSanityCheck.checkDeclare(input,storage);
ConvolveImageMean.horizontal(input,storage,radius);
ConvolveImageMean.vertical(storage,output,radius);
return output;
}
/**
* Applies a median filter.
*
* @param input Input image. Not modified.
* @param output (Optional) Storage for output image, Can be null. Modified.
* @param radius Radius of the median blur function.
* @return Output blurred image.
*/
public static GrayF32 median(GrayF32 input, GrayF32 output, int radius) {
if( radius <= 0 )
throw new IllegalArgumentException("Radius must be > 0");
output = InputSanityCheck.checkDeclare(input,output);
ImplMedianSortNaive.process(input,output,radius,null);
return output;
}
/**
* Applies Gaussian blur.
*
* @param input Input image. Not modified.
* @param output (Optional) Storage for output image, Can be null. Modified.
* @param sigma Gaussian distribution's sigma. If ≤ 0 then will be selected based on radius.
* @param radius Radius of the Gaussian blur function. If ≤ 0 then radius will be determined by sigma.
* @param storage (Optional) Storage for intermediate results. Same size as input image. Can be null.
* @return Output blurred image.
*/
public static GrayF32 gaussian(GrayF32 input, GrayF32 output,
double sigma , int radius,
GrayF32 storage ) {
output = InputSanityCheck.checkDeclare(input,output);
storage = InputSanityCheck.checkDeclare(input,storage);
Kernel1D_F32 kernel = FactoryKernelGaussian.gaussian(Kernel1D_F32.class,sigma, radius);
ConvolveNormalized.horizontal(kernel,input,storage);
ConvolveNormalized.vertical(kernel,storage,output);
return output;
}
/**
* Applies Gaussian blur.
*
* @param input Input image. Not modified.
* @param output (Optional) Storage for output image, Can be null. Modified.
* @param sigma Gaussian distribution's sigma. If ≤ 0 then will be selected based on radius.
* @param radius Radius of the Gaussian blur function. If ≤ 0 then radius will be determined by sigma.
* @param storage (Optional) Storage for intermediate results. Same size as input image. Can be null.
* @return Output blurred image.
*/
public static GrayF64 gaussian(GrayF64 input, GrayF64 output,
double sigma , int radius,
GrayF64 storage ) {
output = InputSanityCheck.checkDeclare(input,output);
storage = InputSanityCheck.checkDeclare(input,storage);
Kernel1D_F64 kernel = FactoryKernelGaussian.gaussian(Kernel1D_F64.class,sigma, radius);
ConvolveNormalized.horizontal(kernel,input,storage);
ConvolveNormalized.vertical(kernel,storage,output);
return output;
}
/**
* Applies mean box filter to a {@link Planar}
*
* @param input Input image. Not modified.
* @param output (Optional) Storage for output image, Can be null. Modified.
* @param radius Radius of the box blur function.
* @param storage (Optional) Storage for intermediate results. Same size as input image. Can be null.
* @param Input image type.
* @return Output blurred image.
*/
public static
Planar mean(Planar input, Planar output, int radius , T storage ) {
if( storage == null )
storage = GeneralizedImageOps.createSingleBand(input.getBandType(),input.width,input.height);
if( output == null )
output = input._createNew(input.width,input.height);
for( int band = 0; band < input.getNumBands(); band++ ) {
GBlurImageOps.median(input.getBand(band),output.getBand(band),radius);
}
return output;
}
/**
* Applies median filter to a {@link Planar}
*
* @param input Input image. Not modified.
* @param output (Optional) Storage for output image, Can be null. Modified.
* @param radius Radius of the median blur function.
* @param Input image type.
* @return Output blurred image.
*/
public static
Planar median(Planar input, Planar output, int radius ) {
if( output == null )
output = input._createNew(input.width,input.height);
for( int band = 0; band < input.getNumBands(); band++ ) {
GBlurImageOps.median(input.getBand(band),output.getBand(band),radius);
}
return output;
}
/**
* Applies Gaussian blur to a {@link Planar}
*
* @param input Input image. Not modified.
* @param output (Optional) Storage for output image, Can be null. Modified.
* @param sigma Gaussian distribution's sigma. If ≤ 0 then will be selected based on radius.
* @param radius Radius of the Gaussian blur function. If ≤ 0 then radius will be determined by sigma.
* @param storage (Optional) Storage for intermediate results. Same size as input image. Can be null.
* @param Input image type.
* @return Output blurred image.
*/
public static
Planar gaussian(Planar input, Planar output, double sigma , int radius, T storage ) {
if( storage == null )
storage = GeneralizedImageOps.createSingleBand(input.getBandType(), input.width, input.height);
if( output == null )
output = input._createNew(input.width,input.height);
for( int band = 0; band < input.getNumBands(); band++ ) {
GBlurImageOps.gaussian(input.getBand(band),output.getBand(band),sigma,radius,storage);
}
return output;
}
}
