/*
* 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.transform.pyramid;
import boofcv.abst.filter.FilterImageInterface;
import boofcv.abst.filter.derivative.ImageGradient;
import boofcv.abst.filter.derivative.ImageHessian;
import boofcv.alg.interpolate.InterpolatePixelS;
import boofcv.alg.transform.pyramid.impl.ImplPyramidOps;
import boofcv.core.image.GeneralizedImageOps;
import boofcv.struct.image.GrayF32;
import boofcv.struct.image.GrayU8;
import boofcv.struct.image.ImageGray;
import boofcv.struct.pyramid.ImagePyramid;
import java.lang.reflect.Array;
/**
* Various operations related to image pyramids.
*
* @author Peter Abeles
*/
public class PyramidOps {
/**
* Creates an array of single band images for each layer in the provided pyramid. Each image will
* be the same size as the corresponding layer in the pyramid.
*
* @param pyramid (Input) Image pyramid
* @param outputType (Input) Output image type
* @param <O> Output image type
* @return An array of images
*/
public static <O extends ImageGray>
O[] declareOutput( ImagePyramid<?> pyramid , Class<O> outputType ) {
O[] ret = (O[])Array.newInstance(outputType,pyramid.getNumLayers());
for( int i = 0; i < ret.length; i++ ) {
int w = pyramid.getWidth(i);
int h = pyramid.getHeight(i);
ret[i] = GeneralizedImageOps.createSingleBand(outputType,w,h);
}
return ret;
}
/**
* Reshapes each image in the array to match the layers in the pyramid
* @param pyramid (Input) Image pyramid
* @param output (Output) List of images which is to be resized
* @param <O> Image type
*/
public static <O extends ImageGray>
void reshapeOutput( ImagePyramid<?> pyramid , O[] output ) {
for( int i = 0; i < output.length; i++ ) {
int w = pyramid.getWidth(i);
int h = pyramid.getHeight(i);
output[i].reshape(w, h);
}
}
/**
* <p>
* Runs an image filter through each layer in the pyramid.
* </p>
*
* <p>
* It is assumed that the output has the same scales as the input. If not
* initialized then it will be initialized. If already initialized it is
* assumed to be setup for the same input image size.
* </p>
*
* @param input Input pyramid.
* @param filter Filter being applied to the pyramid.
* @param output Output pyramid where filter results are saved.
*/
public static <I extends ImageGray, O extends ImageGray>
void filter(ImagePyramid<I> input, FilterImageInterface<I, O> filter, O[] output )
{
for( int i = 0; i < input.getNumLayers(); i++ ) {
I imageIn = input.getLayer(i);
filter.process(imageIn,output[i]);
}
}
/**
* <p>
* Computes the gradient for each image the pyramid.
* </p>
*
* <p>
* It is assumed that the gradient has the same scales as the input. If not
* initialized then it will be initialized. If already initialized it is
* assumed to be setup for the same input image size.
* </p>
*
* @param input Input pyramid.
* @param gradient Computes image gradient
* @param derivX Pyramid where x-derivative is stored.
* @param derivY Pyramid where y-derivative is stored.
*/
public static <I extends ImageGray, O extends ImageGray>
void gradient(ImagePyramid<I> input, ImageGradient<I, O> gradient, O[] derivX, O[] derivY )
{
for( int i = 0; i < input.getNumLayers(); i++ ) {
I imageIn = input.getLayer(i);
gradient.process(imageIn,derivX[i],derivY[i]);
}
}
/**
* <p>
* Computes the hessian (2nd order derivative) for each image the pyramid.
* </p>
*
* @param derivX (Input) Pyramid where x-derivative is stored.
* @param derivY (Input) Pyramid where y-derivative is stored.
* @param hessian (Input) Computes hessian from gradient
* @param derivXX (Output) Second derivative XX
* @param derivYY (Output) Second derivative YY
* @param derivXY (Output) Second derivative XY
*/
public static <I extends ImageGray, O extends ImageGray>
void hessian(O[] derivX, O[] derivY , ImageHessian<O> hessian , O[] derivXX, O[] derivYY , O[] derivXY )
{
for( int i = 0; i < derivX.length; i++ ) {
hessian.process(derivX[i],derivY[i],derivXX[i],derivYY[i],derivXY[i]);
}
}
/**
* Scales down the input by a factor of 2. Every other pixel along both axises is skipped.
*/
public static <T extends ImageGray>
void scaleDown2(T input , T output ) {
if( input instanceof GrayF32) {
ImplPyramidOps.scaleDown2((GrayF32)input,(GrayF32)output);
} else if( input instanceof GrayU8) {
ImplPyramidOps.scaleDown2((GrayU8)input,(GrayU8)output);
} else {
throw new IllegalArgumentException("Image type not yet supported");
}
}
/**
* Scales an image up using interpolation
*
* @param scale How much larger the output image will be.
*/
public static <T extends ImageGray>
void scaleImageUp(T input , T output , int scale, InterpolatePixelS<T> interp ) {
if( scale <= 1 )
throw new IllegalArgumentException("Scale must be >= 2");
if( input instanceof GrayF32) {
ImplPyramidOps.scaleImageUp((GrayF32)input,(GrayF32)output,scale,(InterpolatePixelS)interp);
} else if( input instanceof GrayU8) {
ImplPyramidOps.scaleImageUp((GrayU8)input,(GrayU8)output,scale,(InterpolatePixelS)interp);
} else {
throw new IllegalArgumentException("Image type not yet supported");
}
}
}