PS------Smart blur算法实现

偶尔在网上看到的，关于Smart blur效果的算法实现：

原图

Smart Blur效果图

算法过程如下：

1，每个像素计算一次；

2，每个像素计算以该像素为中心的半径R的正方形区域(边长2R+1)内的方差delta；

3，设定方差阈值Threshold；

4，计算原图的模糊效果图A(均值模糊或者高斯模糊)；

5，如果像素P(x,y)对应的方差delta<Threshold，则按照delta/Threshold的比例将原图与A进行混合或插值，得到结果像素Q(x,y)，如果delta >= Threshold，则Q(x,y) = P(x,y)；

The algorithm is quite straightforward:

1. March through the image pixel by pixel.
2. For each pixel, analyze an adjacent region (say, the adjoining 5 pixel by 5 pixel square).
3. Calculate some metric of pixel variance for that region.
4. Compare the variance to some predetermined threshold value.
5. If the variance exceeds the threshold, do nothing.

6. If the variance is less than the threshold, apply blurring to the source pixel. But vary the amount of blurring according to the variance: low variance, more blurring (high variance, less blurring).

Here's the full code for SmartBlurFilter:

import java.awt.image.Kernel;
import java.awt.image.BufferedImage;
import java.awt.image.ConvolveOp;
import java.awt.Graphics;public class SmartBlurFilter {double SENSITIVITY = 10;int REGION_SIZE = 5;float [] kernelArray = {1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1};Kernel kernel = new Kernel( 9,9, normalizeKernel( kernelArray ) );float [] normalizeKernel( float [] ar ) {int n = 0;for (int i = 0; i < ar.length; i++)n += ar[i];for (int i = 0; i < ar.length; i++)ar[i] /= n;return ar;}public double lerp( double a,double b, double amt) {return a + amt * ( b - a );}public double getLerpAmount( double a, double cutoff ) {if ( a > cutoff )return 1.0;return a / cutoff;}public double rmsError( int [] pixels ) {double ave = 0;for ( int i = 0; i < pixels.length; i++ )ave += ( pixels[ i ] >> 8 ) & 255;ave /= pixels.length;double diff = 0;double accumulator = 0;for ( int i = 0; i < pixels.length; i++ ) {diff = ( ( pixels[ i ] >> 8 ) & 255 ) - ave;diff *= diff;accumulator += diff;}double rms = accumulator / pixels.length;rms = Math.sqrt( rms );return rms;}int [] getSample( BufferedImage image, int x, int y, int size ) {int [] pixels = {};try {BufferedImage subimage = image.getSubimage( x,y, size, size );pixels = subimage.getRGB( 0,0,size,size,null,0,size );}catch( Exception e ) {// will arrive here if we requested// pixels outside the image bounds}return pixels;}int lerpPixel( int oldpixel, int newpixel, double amt ) {int oldRed = ( oldpixel >> 16 ) & 255;int newRed = ( newpixel >> 16 ) & 255;int red = (int) lerp( (double)oldRed, (double)newRed, amt ) & 255;int oldGreen = ( oldpixel >> 8 ) & 255;int newGreen = ( newpixel >> 8 ) & 255;int green = (int) lerp( (double)oldGreen, (double)newGreen, amt ) & 255;int oldBlue = oldpixel & 255;int newBlue = newpixel & 255;int blue = (int) lerp( (double)oldBlue, (double)newBlue, amt ) & 255;return ( red << 16 ) | ( green << 8 ) | blue;}int [] blurImage( BufferedImage image,int [] orig, int [] blur, double sensitivity ) {int newPixel = 0;double amt = 0;int size = REGION_SIZE;for ( int i = 0; i < orig.length; i++ ) {int w = image.getWidth();int [] pix = getSample( image, i % w, i / w, size );if ( pix.length == 0 )continue;amt = getLerpAmount ( rmsError( pix ), sensitivity );newPixel = lerpPixel( blur[ i ], orig[ i ],  amt );orig[ i ] = newPixel;}return orig;}public BufferedImage filter( BufferedImage image ) {ConvolveOp convolver = new ConvolveOp(kernel, ConvolveOp.EDGE_NO_OP,null);// clone image into targetBufferedImage target = new BufferedImage(image.getWidth(), image.getHeight(), image.getType());Graphics g = target.createGraphics();g.drawImage(image, 0, 0, null);g.dispose();int w = target.getWidth();int h = target.getHeight();// get source pixelsint [] pixels = image.getRGB(0, 0, w, h, null, 0, w);// blur the cloned imagetarget = convolver.filter(target, image);// get the blurred pixelsint [] blurryPixels = target.getRGB(0, 0, w, h, null, 0, w);// go thru the image and interpolate valuespixels = blurImage(image, pixels, blurryPixels, SENSITIVITY);// replace original pixels with new onesimage.setRGB(0, 0, w, h, pixels, 0, w);return image;}
}

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