并行计算 SLIC超像素算法(二) 代码分析

这一篇文章主要介绍了SLIC算法的大致分析和理解,提供了源码,供大家复制下载。

目录

部分代码分析

1.RGB -> XYZ

大致分析:

 详细代码:

2.RGB -> LAB 

大致分析:

具体代码:

3.将一个图像中的全部点进行二次转化

大致分析:

具体代码:

4.计算图像中每个像素点的梯度

大致分析:

具体代码:

 5.在 3*3 的领域内选择梯度最小的点作为中心节点

大致思路:

具体代码:

6.移动聚类中心到 3*3 领域中梯度最小的位置

大致分析:

具体代码:

7.计算像素点与聚类中心的距离+分类+重新分类聚类中心

大致分析:

 具体代码:

8.提取图片中每个像素点的R、G、B的值

具体代码:

9.给定K个超像素的SLIC算法

具体代码:

完整代码

SLIC.cpp

SLIC.h

运行结果:


部分代码分析

1.RGB -> XYZ

大致分析:

并行计算 SLIC超像素算法(二) 代码分析_第1张图片

 详细代码:

void SLIC::RGB2XYZ(
	const int&		sR,
	const int&		sG,
	const int&		sB,
	double&			X,
	double&			Y,
	double&			Z)
{
	double R = sR/255.0;
	double G = sG/255.0;
	double B = sB/255.0;

	double r, g, b;

	if(R <= 0.04045)	r = R/12.92;
	else				r = pow((R+0.055)/1.055,2.4);
	if(G <= 0.04045)	g = G/12.92;
	else				g = pow((G+0.055)/1.055,2.4);
	if(B <= 0.04045)	b = B/12.92;
	else				b = pow((B+0.055)/1.055,2.4);

	X = r*0.4124564 + g*0.3575761 + b*0.1804375;
	Y = r*0.2126729 + g*0.7151522 + b*0.0721750;
	Z = r*0.0193339 + g*0.1191920 + b*0.9503041;
}

2.RGB -> LAB 

大致分析:

并行计算 SLIC超像素算法(二) 代码分析_第2张图片

具体代码:

void SLIC::RGB2LAB(const int& sR, const int& sG, const int& sB, double& lval, double& aval, double& bval)
{
	//------------------------
	// sRGB to XYZ conversion
	//------------------------
	double X, Y, Z;
	RGB2XYZ(sR, sG, sB, X, Y, Z);

	//------------------------
	// XYZ to LAB conversion
	//------------------------
	double epsilon = 0.008856;	//actual CIE standard
	double kappa   = 903.3;		//actual CIE standard

	double Xr = 0.950456;	//reference white
	double Yr = 1.0;		//reference white
	double Zr = 1.088754;	//reference white

	double xr = X/Xr;
	double yr = Y/Yr;
	double zr = Z/Zr;

	double fx, fy, fz;
	if(xr > epsilon)	fx = pow(xr, 1.0/3.0);
	else				fx = (kappa*xr + 16.0)/116.0;
	if(yr > epsilon)	fy = pow(yr, 1.0/3.0);
	else				fy = (kappa*yr + 16.0)/116.0;
	if(zr > epsilon)	fz = pow(zr, 1.0/3.0);
	else				fz = (kappa*zr + 16.0)/116.0;

	lval = 116.0*fy-16.0;
	aval = 500.0*(fx-fy);
	bval = 200.0*(fy-fz);
}

3.将一个图像中的全部点进行二次转化

大致分析:

去一个数组的24位的 23~16位, 15~8位,7~0位作为 R、G、B 的值。采用第四步中的方法将其转化为 L、 A、 B的值。

具体代码:

void SLIC::DoRGBtoLABConversion(
	const unsigned int*&		ubuff,
	double*&					lvec,
	double*&					avec,
	double*&					bvec)
{
	int sz = m_width*m_height;
	lvec = new double[sz];
	avec = new double[sz];
	bvec = new double[sz];

	for( int j = 0; j < sz; j++ )
	{
		int r = (ubuff[j] >> 16) & 0xFF;    //取高16位的八位
		int g = (ubuff[j] >>  8) & 0xFF;    //取高8位的八位
		int b = (ubuff[j]      ) & 0xFF;    //取低位的八位

		RGB2LAB( r, g, b, lvec[j], avec[j], bvec[j] );
	}
}

4.计算图像中每个像素点的梯度

大致分析:

具体代码:

void SLIC::DetectLabEdges(
	const double*				lvec,
	const double*				avec,
	const double*				bvec,
	const int&					width,
	const int&					height,
	vector&				edges)
{
	int sz = width*height;

	edges.resize(sz,0);
	for( int j = 1; j < height-1; j++ )
	{
		for( int k = 1; k < width-1; k++ )
		{
			int i = j*width+k;

			double dx = (lvec[i-1]-lvec[i+1])*(lvec[i-1]-lvec[i+1]) +
						(avec[i-1]-avec[i+1])*(avec[i-1]-avec[i+1]) +
						(bvec[i-1]-bvec[i+1])*(bvec[i-1]-bvec[i+1]);

			double dy = (lvec[i-width]-lvec[i+width])*(lvec[i-width]-lvec[i+width]) +
						(avec[i-width]-avec[i+width])*(avec[i-width]-avec[i+width]) +
						(bvec[i-width]-bvec[i+width])*(bvec[i-width]-bvec[i+width]);

			//edges[i] = (sqrt(dx) + sqrt(dy));
			edges[i] = (dx + dy);
		}
	}
}

 5.在 3*3 的领域内选择梯度最小的点作为中心节点

大致思路:

用for循环来遍历图像中的每一个像素点,利用数组来锁定 3*3 的领域。在调用第6步的方法进行对比,如果梯度小的话,就更换中心节点,否则就不变。

具体代码:

void SLIC::PerturbSeeds(
	vector&				kseedsl,
	vector&				kseedsa,
	vector&				kseedsb,
	vector&				kseedsx,
	vector&				kseedsy,
	const vector&		edges)
{
	const int dx8[8] = {-1, -1,  0,  1, 1, 1, 0, -1};
	const int dy8[8] = { 0, -1, -1, -1, 0, 1, 1,  1};
	
	int numseeds = kseedsl.size();

	for( int n = 0; n < numseeds; n++ )
	{
		int ox = kseedsx[n];//original x
		int oy = kseedsy[n];//original y
		int oind = oy*m_width + ox;

		int storeind = oind;
		for( int i = 0; i < 8; i++ )
		{
			int nx = ox+dx8[i];//new x
			int ny = oy+dy8[i];//new y

			if( nx >= 0 && nx < m_width && ny >= 0 && ny < m_height)
			{
				int nind = ny*m_width + nx;
				if( edges[nind] < edges[storeind])
				{
					storeind = nind;
				}
			}
		}
		if(storeind != oind)
		{
			kseedsx[n] = storeind%m_width;
			kseedsy[n] = storeind/m_width;
			kseedsl[n] = m_lvec[storeind];
			kseedsa[n] = m_avec[storeind];
			kseedsb[n] = m_bvec[storeind];
		}
	}
}

6.移动聚类中心到 3*3 领域中梯度最小的位置

大致分析:

利用Sqr(N/K)来遍历整个像素点,然后调用第7步中方法来实现聚类中心的移动。

具体代码:

void SLIC::GetLABXYSeeds_ForGivenK(
	vector&				kseedsl,
	vector&				kseedsa,
	vector&				kseedsb,
	vector&				kseedsx,
	vector&				kseedsy,
	const int&					K,
	const bool&					perturbseeds,
	const vector&		edgemag)
{
	int sz = m_width*m_height;
	double step = sqrt(double(sz)/double(K));
	int T = step;
	int xoff = step/2;
	int yoff = step/2;
	
	int n(0);int r(0);
	for( int y = 0; y < m_height; y++ )
	{
		int Y = y*step + yoff;
		if( Y > m_height-1 ) break;

		for( int x = 0; x < m_width; x++ )
		{
			//int X = x*step + xoff;//square grid
			int X = x*step + (xoff<<(r&0x1));//hex grid
			if(X > m_width-1) break;

			int i = Y*m_width + X;

			//_ASSERT(n < K);
			
			//kseedsl[n] = m_lvec[i];
			//kseedsa[n] = m_avec[i];
			//kseedsb[n] = m_bvec[i];
			//kseedsx[n] = X;
			//kseedsy[n] = Y;
			kseedsl.push_back(m_lvec[i]);
			kseedsa.push_back(m_avec[i]);
			kseedsb.push_back(m_bvec[i]);
			kseedsx.push_back(X);
			kseedsy.push_back(Y);
			n++;
		}
		r++;
	}

	if(perturbseeds)
	{
		PerturbSeeds(kseedsl, kseedsa, kseedsb, kseedsx, kseedsy, edgemag);
	}
}

7.计算像素点与聚类中心的距离+分类+重新分类聚类中心

大致分析:

距离使用的是欧式距离,总距离 由 dc颜色距离与 ds空间距离两部分组成。公式如下:

并行计算 SLIC超像素算法(二) 代码分析_第3张图片

标记每个像素点的类别为距离其最小的聚类中心的类别。

计算属于同一个聚类的所有像素点的平均向量值,重新得到聚类中心 。

 具体代码:

void SLIC::PerformSuperpixelSegmentation_VariableSandM(
	vector&				kseedsl,
	vector&				kseedsa,
	vector&				kseedsb,
	vector&				kseedsx,
	vector&				kseedsy,
	int*						klabels,
	const int&					STEP,
	const int&					NUMITR)
{
	int sz = m_width*m_height;
	const int numk = kseedsl.size();
	//double cumerr(99999.9);
	int numitr(0);

	//----------------
	int offset = STEP;
	if(STEP < 10) offset = STEP*1.5;
	//----------------

	vector sigmal(numk, 0);
	vector sigmaa(numk, 0);
	vector sigmab(numk, 0);
	vector sigmax(numk, 0);
	vector sigmay(numk, 0);
	vector clustersize(numk, 0);
	vector inv(numk, 0);//to store 1/clustersize[k] values
	vector distxy(sz, DBL_MAX);
	vector distlab(sz, DBL_MAX);
	vector distvec(sz, DBL_MAX);
	vector maxlab(numk, 10*10);//THIS IS THE VARIABLE VALUE OF M, just start with 10
	vector maxxy(numk, STEP*STEP);//THIS IS THE VARIABLE VALUE OF M, just start with 10

	double invxywt = 1.0/(STEP*STEP);//NOTE: this is different from how usual SLIC/LKM works

	while( numitr < NUMITR )
	{
		//------
		//cumerr = 0;
		numitr++;
		//------

		distvec.assign(sz, DBL_MAX);
		for( int n = 0; n < numk; n++ )
		{
			int y1 = max(0,			(int)(kseedsy[n]-offset));
			int y2 = min(m_height,	(int)(kseedsy[n]+offset));
			int x1 = max(0,			(int)(kseedsx[n]-offset));
			int x2 = min(m_width,	(int)(kseedsx[n]+offset));

			for( int y = y1; y < y2; y++ )
			{
				for( int x = x1; x < x2; x++ )
				{
					int i = y*m_width + x;
					//_ASSERT( y < m_height && x < m_width && y >= 0 && x >= 0 );

					double l = m_lvec[i];
					double a = m_avec[i];
					double b = m_bvec[i];

					distlab[i] =	(l - kseedsl[n])*(l - kseedsl[n]) +
									(a - kseedsa[n])*(a - kseedsa[n]) +
									(b - kseedsb[n])*(b - kseedsb[n]);

					distxy[i] =		(x - kseedsx[n])*(x - kseedsx[n]) +
									(y - kseedsy[n])*(y - kseedsy[n]);

					//------------------------------------------------------------------------
					double dist = distlab[i]/maxlab[n] + distxy[i]*invxywt;//only varying m, prettier superpixels
					//double dist = distlab[i]/maxlab[n] + distxy[i]/maxxy[n];//varying both m and S
					//------------------------------------------------------------------------
					
					if( dist < distvec[i] )
					{
						distvec[i] = dist;
						klabels[i]  = n;
					}
				}
			}
		}
		//-----------------------------------------------------------------
		// Assign the max color distance for a cluster
		//-----------------------------------------------------------------
		if(0 == numitr)
		{
			maxlab.assign(numk,1);
			maxxy.assign(numk,1);
		}
		{for( int i = 0; i < sz; i++ )
		{
			if(maxlab[klabels[i]] < distlab[i]) maxlab[klabels[i]] = distlab[i];
			if(maxxy[klabels[i]] < distxy[i]) maxxy[klabels[i]] = distxy[i];
		}}
		//-----------------------------------------------------------------
		// Recalculate the centroid and store in the seed values
		//-----------------------------------------------------------------
		sigmal.assign(numk, 0);
		sigmaa.assign(numk, 0);
		sigmab.assign(numk, 0);
		sigmax.assign(numk, 0);
		sigmay.assign(numk, 0);
		clustersize.assign(numk, 0);

		for( int j = 0; j < sz; j++ )
		{
			int temp = klabels[j];
			//_ASSERT(klabels[j] >= 0);
			sigmal[klabels[j]] += m_lvec[j];
			sigmaa[klabels[j]] += m_avec[j];
			sigmab[klabels[j]] += m_bvec[j];
			sigmax[klabels[j]] += (j%m_width);
			sigmay[klabels[j]] += (j/m_width);

			clustersize[klabels[j]]++;
		}

		{for( int k = 0; k < numk; k++ )
		{
			//_ASSERT(clustersize[k] > 0);
			if( clustersize[k] <= 0 ) clustersize[k] = 1;
			inv[k] = 1.0/double(clustersize[k]);//computing inverse now to multiply, than divide later
		}}
		
		{for( int k = 0; k < numk; k++ )
		{
			kseedsl[k] = sigmal[k]*inv[k];
			kseedsa[k] = sigmaa[k]*inv[k];
			kseedsb[k] = sigmab[k]*inv[k];
			kseedsx[k] = sigmax[k]*inv[k];
			kseedsy[k] = sigmay[k]*inv[k];
		}}
	}
}

8.提取图片中每个像素点的R、G、B的值

具体代码:

void SLIC::SaveSuperpixelLabels2PPM(
	char*                           filename, 
	int *                           labels, 
	const int                       width, 
	const int                       height)
{
    FILE* fp;
    char header[20];
 
    fp = fopen(filename, "wb");
 
    // write the PPM header info, such as type, width, height and maximum
    fprintf(fp,"P6\n%d %d\n255\n", width, height);
 
    // write the RGB data
    unsigned char *rgb = new unsigned char [ (width)*(height)*3 ];
    int k = 0;
	unsigned char c = 0;
    for ( int i = 0; i < (height); i++ ) {
        for ( int j = 0; j < (width); j++ ) {
			c = (unsigned char)(labels[k]);
            rgb[i*(width)*3 + j*3 + 2] = labels[k] >> 16 & 0xff;  // r
            rgb[i*(width)*3 + j*3 + 1] = labels[k] >> 8  & 0xff;  // g
            rgb[i*(width)*3 + j*3 + 0] = labels[k]       & 0xff;  // b

			// rgb[i*(width) + j + 0] = c;
            k++;
        }
    }
    fwrite(rgb, width*height*3, 1, fp);

    delete [] rgb;
 
    fclose(fp);

}

9.给定K个超像素的SLIC算法

具体代码:

void SLIC::PerformSLICO_ForGivenK(
	const unsigned int*			ubuff,
	const int					width,
	const int					height,
	int*						klabels,
	int&						numlabels,
	const int&					K,//required number of superpixels
	const double&				m)//weight given to spatial distance
{
	vector kseedsl(0);
	vector kseedsa(0);
	vector kseedsb(0);
	vector kseedsx(0);
	vector kseedsy(0);

	//--------------------------------------------------
	m_width  = width;
	m_height = height;
	int sz = m_width*m_height;
	//--------------------------------------------------
	//if(0 == klabels) klabels = new int[sz];
	for( int s = 0; s < sz; s++ ) klabels[s] = -1;
	//--------------------------------------------------
	if(1)//LAB
	{
		DoRGBtoLABConversion(ubuff, m_lvec, m_avec, m_bvec); //RGB->LAB
	}
	else//RGB
	{
		m_lvec = new double[sz]; m_avec = new double[sz]; m_bvec = new double[sz];
		for( int i = 0; i < sz; i++ )
		{
			m_lvec[i] = ubuff[i] >> 16 & 0xff;
			m_avec[i] = ubuff[i] >>  8 & 0xff;
			m_bvec[i] = ubuff[i]       & 0xff;
		}
	}
	//--------------------------------------------------

	bool perturbseeds(true);
	vector edgemag(0);
	if(perturbseeds) DetectLabEdges(m_lvec, m_avec, m_bvec, m_width, m_height, edgemag);//计算每个点的像素梯度
	GetLABXYSeeds_ForGivenK(kseedsl, kseedsa, kseedsb, kseedsx, kseedsy, K, perturbseeds, edgemag);//移动聚类中心到 3*3 领域中梯度最小的位置

	int STEP = sqrt(double(sz)/double(K)) + 2.0;//adding a small value in the even the STEP size is too small.
	PerformSuperpixelSegmentation_VariableSandM(kseedsl,kseedsa,kseedsb,kseedsx,kseedsy,klabels,STEP,10);//分类
	numlabels = kseedsl.size();

	int* nlabels = new int[sz];
	EnforceLabelConnectivity(klabels, m_width, m_height, nlabels, numlabels, K);
	{for(int i = 0; i < sz; i++ ) klabels[i] = nlabels[i];}
	if(nlabels) delete [] nlabels;
}

完整代码

SLIC.cpp

// SLIC.cpp: implementation of the SLIC class.
//===========================================================================
// This code implements the zero parameter superpixel segmentation technique
// described in:
//
//
//
// "SLIC Superpixels Compared to State-of-the-art Superpixel Methods"
//
// Radhakrishna Achanta, Appu Shaji, Kevin Smith, Aurelien Lucchi, Pascal Fua,
// and Sabine Susstrunk,
//
// IEEE TPAMI, Volume 34, Issue 11, Pages 2274-2282, November 2012.
//
// https://www.epfl.ch/labs/ivrl/research/slic-superpixels/
//===========================================================================
// Copyright (c) 2013 Radhakrishna Achanta.
//
// For commercial use please contact the author:
//
// Email: [email protected]
//===========================================================================

#include 
#include 
#include 
#include 
#include 
#include "SLIC.h"
#include 
#include 


typedef chrono::high_resolution_clock Clock;

// For superpixels
const int dx4[4] = {-1,  0,  1,  0};
const int dy4[4] = { 0, -1,  0,  1};
//const int dx8[8] = {-1, -1,  0,  1, 1, 1, 0, -1};
//const int dy8[8] = { 0, -1, -1, -1, 0, 1, 1,  1};

// For supervoxels
const int dx10[10] = {-1,  0,  1,  0, -1,  1,  1, -1,  0, 0};
const int dy10[10] = { 0, -1,  0,  1, -1, -1,  1,  1,  0, 0};
const int dz10[10] = { 0,  0,  0,  0,  0,  0,  0,  0, -1, 1};

//
// Construction/Destruction
//

SLIC::SLIC()
{
	m_lvec = NULL;
	m_avec = NULL;
	m_bvec = NULL;

	m_lvecvec = NULL;
	m_avecvec = NULL;
	m_bvecvec = NULL;
}

SLIC::~SLIC()
{
	if(m_lvec) delete [] m_lvec;
	if(m_avec) delete [] m_avec;
	if(m_bvec) delete [] m_bvec;


	if(m_lvecvec)
	{
		for( int d = 0; d < m_depth; d++ ) delete [] m_lvecvec[d];
		delete [] m_lvecvec;
	}
	if(m_avecvec)
	{
		for( int d = 0; d < m_depth; d++ ) delete [] m_avecvec[d];
		delete [] m_avecvec;
	}
	if(m_bvecvec)
	{
		for( int d = 0; d < m_depth; d++ ) delete [] m_bvecvec[d];
		delete [] m_bvecvec;
	}
}

//==============================================================================
///	RGB2XYZ
///
/// sRGB (D65 illuninant assumption) to XYZ conversion
//==============================================================================
void SLIC::RGB2XYZ(
	const int&		sR,
	const int&		sG,
	const int&		sB,
	double&			X,
	double&			Y,
	double&			Z)
{
	double R = sR/255.0;
	double G = sG/255.0;
	double B = sB/255.0;

	double r, g, b;

	if(R <= 0.04045)	r = R/12.92;
	else				r = pow((R+0.055)/1.055,2.4);
	if(G <= 0.04045)	g = G/12.92;
	else				g = pow((G+0.055)/1.055,2.4);
	if(B <= 0.04045)	b = B/12.92;
	else				b = pow((B+0.055)/1.055,2.4);

	X = r*0.4124564 + g*0.3575761 + b*0.1804375;
	Y = r*0.2126729 + g*0.7151522 + b*0.0721750;
	Z = r*0.0193339 + g*0.1191920 + b*0.9503041;
}

//===========================================================================
///	RGB2LAB
//===========================================================================
void SLIC::RGB2LAB(const int& sR, const int& sG, const int& sB, double& lval, double& aval, double& bval)
{
	//------------------------
	// sRGB to XYZ conversion
	//------------------------
	double X, Y, Z;
	RGB2XYZ(sR, sG, sB, X, Y, Z);

	//------------------------
	// XYZ to LAB conversion
	//------------------------
	double epsilon = 0.008856;	//actual CIE standard
	double kappa   = 903.3;		//actual CIE standard

	double Xr = 0.950456;	//reference white
	double Yr = 1.0;		//reference white
	double Zr = 1.088754;	//reference white

	double xr = X/Xr;
	double yr = Y/Yr;
	double zr = Z/Zr;

	double fx, fy, fz;
	if(xr > epsilon)	fx = pow(xr, 1.0/3.0);
	else				fx = (kappa*xr + 16.0)/116.0;
	if(yr > epsilon)	fy = pow(yr, 1.0/3.0);
	else				fy = (kappa*yr + 16.0)/116.0;
	if(zr > epsilon)	fz = pow(zr, 1.0/3.0);
	else				fz = (kappa*zr + 16.0)/116.0;

	lval = 116.0*fy-16.0;
	aval = 500.0*(fx-fy);
	bval = 200.0*(fy-fz);
}

//===========================================================================
///	DoRGBtoLABConversion
///
///	For whole image: overlaoded floating point version
//===========================================================================
void SLIC::DoRGBtoLABConversion(
	const unsigned int*&		ubuff,
	double*&					lvec,
	double*&					avec,
	double*&					bvec)
{
	int sz = m_width*m_height;
	lvec = new double[sz];
	avec = new double[sz];
	bvec = new double[sz];

	for( int j = 0; j < sz; j++ )
	{
		int r = (ubuff[j] >> 16) & 0xFF;    //取高16位的八位
		int g = (ubuff[j] >>  8) & 0xFF;    //取高8位的八位
		int b = (ubuff[j]      ) & 0xFF;    //取低位的八位

		RGB2LAB( r, g, b, lvec[j], avec[j], bvec[j] );
	}
}

//==============================================================================
///	DetectLabEdges
//==============================================================================
void SLIC::DetectLabEdges(
	const double*				lvec,
	const double*				avec,
	const double*				bvec,
	const int&					width,
	const int&					height,
	vector&				edges)
{
	int sz = width*height;

	edges.resize(sz,0);
	for( int j = 1; j < height-1; j++ )
	{
		for( int k = 1; k < width-1; k++ )
		{
			int i = j*width+k;

			double dx = (lvec[i-1]-lvec[i+1])*(lvec[i-1]-lvec[i+1]) +
						(avec[i-1]-avec[i+1])*(avec[i-1]-avec[i+1]) +
						(bvec[i-1]-bvec[i+1])*(bvec[i-1]-bvec[i+1]);

			double dy = (lvec[i-width]-lvec[i+width])*(lvec[i-width]-lvec[i+width]) +
						(avec[i-width]-avec[i+width])*(avec[i-width]-avec[i+width]) +
						(bvec[i-width]-bvec[i+width])*(bvec[i-width]-bvec[i+width]);

			//edges[i] = (sqrt(dx) + sqrt(dy));
			edges[i] = (dx + dy);
		}
	}
}

//===========================================================================
///	PerturbSeeds
//===========================================================================
void SLIC::PerturbSeeds(
	vector&				kseedsl,
	vector&				kseedsa,
	vector&				kseedsb,
	vector&				kseedsx,
	vector&				kseedsy,
	const vector&		edges)
{
	const int dx8[8] = {-1, -1,  0,  1, 1, 1, 0, -1};
	const int dy8[8] = { 0, -1, -1, -1, 0, 1, 1,  1};
	
	int numseeds = kseedsl.size();

	for( int n = 0; n < numseeds; n++ )
	{
		int ox = kseedsx[n];//original x
		int oy = kseedsy[n];//original y
		int oind = oy*m_width + ox;

		int storeind = oind;
		for( int i = 0; i < 8; i++ )
		{
			int nx = ox+dx8[i];//new x
			int ny = oy+dy8[i];//new y

			if( nx >= 0 && nx < m_width && ny >= 0 && ny < m_height)
			{
				int nind = ny*m_width + nx;
				if( edges[nind] < edges[storeind])
				{
					storeind = nind;
				}
			}
		}
		if(storeind != oind)
		{
			kseedsx[n] = storeind%m_width;
			kseedsy[n] = storeind/m_width;
			kseedsl[n] = m_lvec[storeind];
			kseedsa[n] = m_avec[storeind];
			kseedsb[n] = m_bvec[storeind];
		}
	}
}

//===========================================================================
///	GetLABXYSeeds_ForGivenK
///
/// The k seed values are taken as uniform spatial pixel samples.
//===========================================================================
void SLIC::GetLABXYSeeds_ForGivenK(
	vector&				kseedsl,
	vector&				kseedsa,
	vector&				kseedsb,
	vector&				kseedsx,
	vector&				kseedsy,
	const int&					K,
	const bool&					perturbseeds,
	const vector&		edgemag)
{
	int sz = m_width*m_height;
	double step = sqrt(double(sz)/double(K));
	int T = step;
	int xoff = step/2;
	int yoff = step/2;
	
	int n(0);int r(0);
	for( int y = 0; y < m_height; y++ )
	{
		int Y = y*step + yoff;
		if( Y > m_height-1 ) break;

		for( int x = 0; x < m_width; x++ )
		{
			//int X = x*step + xoff;//square grid
			int X = x*step + (xoff<<(r&0x1));//hex grid
			if(X > m_width-1) break;

			int i = Y*m_width + X;

			//_ASSERT(n < K);
			
			//kseedsl[n] = m_lvec[i];
			//kseedsa[n] = m_avec[i];
			//kseedsb[n] = m_bvec[i];
			//kseedsx[n] = X;
			//kseedsy[n] = Y;
			kseedsl.push_back(m_lvec[i]);
			kseedsa.push_back(m_avec[i]);
			kseedsb.push_back(m_bvec[i]);
			kseedsx.push_back(X);
			kseedsy.push_back(Y);
			n++;
		}
		r++;
	}

	if(perturbseeds)
	{
		PerturbSeeds(kseedsl, kseedsa, kseedsb, kseedsx, kseedsy, edgemag);
	}
}

//===========================================================================
///	PerformSuperpixelSegmentation_VariableSandM
///
///	Magic SLIC - no parameters
///
///	Performs k mean segmentation. It is fast because it looks locally, not
/// over the entire image.
/// This function picks the maximum value of color distance as compact factor
/// M and maximum pixel distance as grid step size S from each cluster (13 April 2011).
/// So no need to input a constant value of M and S. There are two clear
/// advantages:
///
/// [1] The algorithm now better handles both textured and non-textured regions
/// [2] There is not need to set any parameters!!!
///
/// SLICO (or SLIC Zero) dynamically varies only the compactness factor S,
/// not the step size S.
//===========================================================================
void SLIC::PerformSuperpixelSegmentation_VariableSandM(
	vector&				kseedsl,
	vector&				kseedsa,
	vector&				kseedsb,
	vector&				kseedsx,
	vector&				kseedsy,
	int*						klabels,
	const int&					STEP,
	const int&					NUMITR)
{
	int sz = m_width*m_height;
	const int numk = kseedsl.size();
	//double cumerr(99999.9);
	int numitr(0);

	//----------------
	int offset = STEP;
	if(STEP < 10) offset = STEP*1.5;
	//----------------

	vector sigmal(numk, 0);
	vector sigmaa(numk, 0);
	vector sigmab(numk, 0);
	vector sigmax(numk, 0);
	vector sigmay(numk, 0);
	vector clustersize(numk, 0);
	vector inv(numk, 0);//to store 1/clustersize[k] values
	vector distxy(sz, DBL_MAX);
	vector distlab(sz, DBL_MAX);
	vector distvec(sz, DBL_MAX);
	vector maxlab(numk, 10*10);//THIS IS THE VARIABLE VALUE OF M, just start with 10
	vector maxxy(numk, STEP*STEP);//THIS IS THE VARIABLE VALUE OF M, just start with 10

	double invxywt = 1.0/(STEP*STEP);//NOTE: this is different from how usual SLIC/LKM works

	while( numitr < NUMITR )
	{
		//------
		//cumerr = 0;
		numitr++;
		//------

		distvec.assign(sz, DBL_MAX);
		for( int n = 0; n < numk; n++ )
		{
			int y1 = max(0,			(int)(kseedsy[n]-offset));
			int y2 = min(m_height,	(int)(kseedsy[n]+offset));
			int x1 = max(0,			(int)(kseedsx[n]-offset));
			int x2 = min(m_width,	(int)(kseedsx[n]+offset));

			for( int y = y1; y < y2; y++ )
			{
				for( int x = x1; x < x2; x++ )
				{
					int i = y*m_width + x;
					//_ASSERT( y < m_height && x < m_width && y >= 0 && x >= 0 );

					double l = m_lvec[i];
					double a = m_avec[i];
					double b = m_bvec[i];

					distlab[i] =	(l - kseedsl[n])*(l - kseedsl[n]) +
									(a - kseedsa[n])*(a - kseedsa[n]) +
									(b - kseedsb[n])*(b - kseedsb[n]);

					distxy[i] =		(x - kseedsx[n])*(x - kseedsx[n]) +
									(y - kseedsy[n])*(y - kseedsy[n]);

					//------------------------------------------------------------------------
					double dist = distlab[i]/maxlab[n] + distxy[i]*invxywt;//only varying m, prettier superpixels
					//double dist = distlab[i]/maxlab[n] + distxy[i]/maxxy[n];//varying both m and S
					//------------------------------------------------------------------------
					
					if( dist < distvec[i] )
					{
						distvec[i] = dist;
						klabels[i]  = n;
					}
				}
			}
		}
		//-----------------------------------------------------------------
		// Assign the max color distance for a cluster
		//-----------------------------------------------------------------
		if(0 == numitr)
		{
			maxlab.assign(numk,1);
			maxxy.assign(numk,1);
		}
		{for( int i = 0; i < sz; i++ )
		{
			if(maxlab[klabels[i]] < distlab[i]) maxlab[klabels[i]] = distlab[i];
			if(maxxy[klabels[i]] < distxy[i]) maxxy[klabels[i]] = distxy[i];
		}}
		//-----------------------------------------------------------------
		// Recalculate the centroid and store in the seed values
		//-----------------------------------------------------------------
		sigmal.assign(numk, 0);
		sigmaa.assign(numk, 0);
		sigmab.assign(numk, 0);
		sigmax.assign(numk, 0);
		sigmay.assign(numk, 0);
		clustersize.assign(numk, 0);

		for( int j = 0; j < sz; j++ )
		{
			int temp = klabels[j];
			//_ASSERT(klabels[j] >= 0);
			sigmal[klabels[j]] += m_lvec[j];
			sigmaa[klabels[j]] += m_avec[j];
			sigmab[klabels[j]] += m_bvec[j];
			sigmax[klabels[j]] += (j%m_width);
			sigmay[klabels[j]] += (j/m_width);

			clustersize[klabels[j]]++;
		}

		{for( int k = 0; k < numk; k++ )
		{
			//_ASSERT(clustersize[k] > 0);
			if( clustersize[k] <= 0 ) clustersize[k] = 1;
			inv[k] = 1.0/double(clustersize[k]);//computing inverse now to multiply, than divide later
		}}
		
		{for( int k = 0; k < numk; k++ )
		{
			kseedsl[k] = sigmal[k]*inv[k];
			kseedsa[k] = sigmaa[k]*inv[k];
			kseedsb[k] = sigmab[k]*inv[k];
			kseedsx[k] = sigmax[k]*inv[k];
			kseedsy[k] = sigmay[k]*inv[k];
		}}
	}
}

//===========================================================================
///	SaveSuperpixelLabels2PGM
///
///	Save labels to PGM in raster scan order.
//===========================================================================
void SLIC::SaveSuperpixelLabels2PPM(
	char*                           filename, 
	int *                           labels, 
	const int                       width, 
	const int                       height)
{
    FILE* fp;
    char header[20];
 
    fp = fopen(filename, "wb");
 
    // write the PPM header info, such as type, width, height and maximum
    fprintf(fp,"P6\n%d %d\n255\n", width, height);
 
    // write the RGB data
    unsigned char *rgb = new unsigned char [ (width)*(height)*3 ];
    int k = 0;
	unsigned char c = 0;
    for ( int i = 0; i < (height); i++ ) {
        for ( int j = 0; j < (width); j++ ) {
			c = (unsigned char)(labels[k]);
            rgb[i*(width)*3 + j*3 + 2] = labels[k] >> 16 & 0xff;  // r
            rgb[i*(width)*3 + j*3 + 1] = labels[k] >> 8  & 0xff;  // g
            rgb[i*(width)*3 + j*3 + 0] = labels[k]       & 0xff;  // b

			// rgb[i*(width) + j + 0] = c;
            k++;
        }
    }
    fwrite(rgb, width*height*3, 1, fp);

    delete [] rgb;
 
    fclose(fp);

}

//===========================================================================
///	EnforceLabelConnectivity
///
///		1. finding an adjacent label for each new component at the start
///		2. if a certain component is too small, assigning the previously found
///		    adjacent label to this component, and not incrementing the label.
//===========================================================================
void SLIC::EnforceLabelConnectivity(
	const int*					labels,//input labels that need to be corrected to remove stray labels
	const int&					width,
	const int&					height,
	int*						nlabels,//new labels
	int&						numlabels,//the number of labels changes in the end if segments are removed
	const int&					K) //the number of superpixels desired by the user
{
//	const int dx8[8] = {-1, -1,  0,  1, 1, 1, 0, -1};
//	const int dy8[8] = { 0, -1, -1, -1, 0, 1, 1,  1};

	const int dx4[4] = {-1,  0,  1,  0};
	const int dy4[4] = { 0, -1,  0,  1};

	const int sz = width*height;
	const int SUPSZ = sz/K;
	//nlabels.resize(sz, -1);
	for( int i = 0; i < sz; i++ ) nlabels[i] = -1;
	int label(0);
	int* xvec = new int[sz];
	int* yvec = new int[sz];
	int oindex(0);
	int adjlabel(0);//adjacent label
	for( int j = 0; j < height; j++ )
	{
		for( int k = 0; k < width; k++ )
		{
			if( 0 > nlabels[oindex] )
			{
				nlabels[oindex] = label;
				//--------------------
				// Start a new segment
				//--------------------
				xvec[0] = k;
				yvec[0] = j;
				//-------------------------------------------------------
				// Quickly find an adjacent label for use later if needed
				//-------------------------------------------------------
				{for( int n = 0; n < 4; n++ )
				{
					int x = xvec[0] + dx4[n];
					int y = yvec[0] + dy4[n];
					if( (x >= 0 && x < width) && (y >= 0 && y < height) )
					{
						int nindex = y*width + x;
						if(nlabels[nindex] >= 0) adjlabel = nlabels[nindex];
					}
				}}

				int count(1);
				for( int c = 0; c < count; c++ )
				{
					for( int n = 0; n < 4; n++ )
					{
						int x = xvec[c] + dx4[n];
						int y = yvec[c] + dy4[n];

						if( (x >= 0 && x < width) && (y >= 0 && y < height) )
						{
							int nindex = y*width + x;

							if( 0 > nlabels[nindex] && labels[oindex] == labels[nindex] )
							{
								xvec[count] = x;
								yvec[count] = y;
								nlabels[nindex] = label;
								count++;
							}
						}

					}
				}
				//-------------------------------------------------------
				// If segment size is less then a limit, assign an
				// adjacent label found before, and decrement label count.
				//-------------------------------------------------------
				if(count <= SUPSZ >> 2)
				{
					for( int c = 0; c < count; c++ )
					{
						int ind = yvec[c]*width+xvec[c];
						nlabels[ind] = adjlabel;
					}
					label--;
				}
				label++;
			}
			oindex++;
		}
	}
	numlabels = label;

	if(xvec) delete [] xvec;
	if(yvec) delete [] yvec;
}

//===========================================================================
///	PerformSLICO_ForGivenK
///
/// Zero parameter SLIC algorithm for a given number K of superpixels.
//===========================================================================
void SLIC::PerformSLICO_ForGivenK(
	const unsigned int*			ubuff,
	const int					width,
	const int					height,
	int*						klabels,
	int&						numlabels,
	const int&					K,//required number of superpixels
	const double&				m)//weight given to spatial distance
{
	vector kseedsl(0);
	vector kseedsa(0);
	vector kseedsb(0);
	vector kseedsx(0);
	vector kseedsy(0);

	//--------------------------------------------------
	m_width  = width;
	m_height = height;
	int sz = m_width*m_height;
	//--------------------------------------------------
	//if(0 == klabels) klabels = new int[sz];
	for( int s = 0; s < sz; s++ ) klabels[s] = -1;
	//--------------------------------------------------
	if(1)//LAB
	{
		DoRGBtoLABConversion(ubuff, m_lvec, m_avec, m_bvec); //RGB->LAB
	}
	else//RGB
	{
		m_lvec = new double[sz]; m_avec = new double[sz]; m_bvec = new double[sz];
		for( int i = 0; i < sz; i++ )
		{
			m_lvec[i] = ubuff[i] >> 16 & 0xff;
			m_avec[i] = ubuff[i] >>  8 & 0xff;
			m_bvec[i] = ubuff[i]       & 0xff;
		}
	}
	//--------------------------------------------------

	bool perturbseeds(true);
	vector edgemag(0);
	if(perturbseeds) DetectLabEdges(m_lvec, m_avec, m_bvec, m_width, m_height, edgemag);//计算每个点的像素梯度
	GetLABXYSeeds_ForGivenK(kseedsl, kseedsa, kseedsb, kseedsx, kseedsy, K, perturbseeds, edgemag);//移动聚类中心到 3*3 领域中梯度最小的位置

	int STEP = sqrt(double(sz)/double(K)) + 2.0;//adding a small value in the even the STEP size is too small.
	PerformSuperpixelSegmentation_VariableSandM(kseedsl,kseedsa,kseedsb,kseedsx,kseedsy,klabels,STEP,10);//分类
	numlabels = kseedsl.size();

	int* nlabels = new int[sz];
	EnforceLabelConnectivity(klabels, m_width, m_height, nlabels, numlabels, K);
	{for(int i = 0; i < sz; i++ ) klabels[i] = nlabels[i];}
	if(nlabels) delete [] nlabels;
}

//===========================================================================
/// Load PPM file
///
/// 
//===========================================================================
void LoadPPM(char* filename, unsigned int** data, int* width, int* height)
{
    char header[1024];
    FILE* fp = NULL;
    int line = 0;
 
    fp = fopen(filename, "rb");
 
    // read the image type, such as: P6
    // skip the comment lines
    while (line < 2) {    
        fgets(header, 1024, fp);
        if (header[0] != '#') {
            ++line;
        }
    }
    // read width and height
    sscanf(header,"%d %d\n", width, height);
 
    // read the maximum of pixels
    fgets(header, 20, fp);
 
    // get rgb data
    unsigned char *rgb = new unsigned char [ (*width)*(*height)*3 ];
    fread(rgb, (*width)*(*height)*3, 1, fp);

    *data = new unsigned int [ (*width)*(*height)*4 ];
    int k = 0;
    for ( int i = 0; i < (*height); i++ ) {
        for ( int j = 0; j < (*width); j++ ) {
            unsigned char *p = rgb + i*(*width)*3 + j*3;
                                      // a ( skipped )
            (*data)[k]  = p[2] << 16; // r
            (*data)[k] |= p[1] << 8;  // g
            (*data)[k] |= p[0];       // b
            k++;
        }
    }

    // ofc, later, you'll have to cleanup
    delete [] rgb;
 
    fclose(fp);
}

//===========================================================================
/// Load PPM file
///
/// 
//===========================================================================
int CheckLabelswithPPM(char* filename, int* labels, int width, int height)
{
    char header[1024];
    FILE* fp = NULL;
    int line = 0, ground = 0;
 
    fp = fopen(filename, "rb");
 
    // read the image type, such as: P6
    // skip the comment lines
    while (line < 2) {    
        fgets(header, 1024, fp);
        if (header[0] != '#') {
            ++line;
        }
    }
    // read width and height
	int w(0);
	int h(0);
    sscanf(header,"%d %d\n", &w, &h);
	if (w != width || h != height) return -1;
 
    // read the maximum of pixels
    fgets(header, 20, fp);
 
    // get rgb data
    unsigned char *rgb = new unsigned char [ (w)*(h)*3 ];
    fread(rgb, (w)*(h)*3, 1, fp);

    int num = 0, k = 0;
    for ( int i = 0; i < (h); i++ ) {
        for ( int j = 0; j < (w); j++ ) {
            unsigned char *p = rgb + i*(w)*3 + j*3;
                                  // a ( skipped )
            ground  = p[2] << 16; // r
            ground |= p[1] << 8;  // g
            ground |= p[0];       // b
            
			if (ground != labels[k])
				num++;

			k++;
        }
    }

    // ofc, later, you'll have to cleanup
    delete [] rgb;
 
    fclose(fp);

	return num;
}

//===========================================================================
///	The main function
///
//===========================================================================
int main (int argc, char **argv)
{

	unsigned int* img = NULL;
	int width(0);
	int height(0);

	LoadPPM((char *)"../input_image.ppm", &img, &width, &height);
	if (width == 0 || height == 0) return -1;
//    cout << "sss" << endl;

	int sz = width*height;
	int* labels = new int[sz];
	int numlabels(0);
	SLIC slic;
	int m_spcount;
	double m_compactness;
	m_spcount = 200;
	m_compactness = 10.0;
    auto startTime = Clock::now();
	slic.PerformSLICO_ForGivenK(img, width, height, labels, numlabels, m_spcount, m_compactness);//for a given number K of superpixels
    auto endTime = Clock::now();
    auto compTime = chrono::duration_cast(endTime - startTime);
    cout <<  "Computing time=" << compTime.count()/1000 << " ms" << endl;

	int num = CheckLabelswithPPM((char *)"../check.ppm", labels, width, height);
	if (num < 0) {
		cout <<  "The result for labels is different from output_labels.ppm." << endl;
	} else {
		cout <<  "There are " << num << " points' labels are different from original file." << endl;
	}
	
	slic.SaveSuperpixelLabels2PPM((char *)"../output_labels.ppm", labels, width, height);

	if(labels) delete [] labels;
	
	if(img) delete [] img;

	return 0;
}

SLIC.h

// SLIC.h: interface for the SLIC class.
//===========================================================================
// This code implements the zero parameter superpixel segmentation technique
// described in:
//
//
//
// "SLIC Superpixels Compared to State-of-the-art Superpixel Methods"
//
// Radhakrishna Achanta, Appu Shaji, Kevin Smith, Aurelien Lucchi, Pascal Fua,
// and Sabine Susstrunk,
//
// IEEE TPAMI, Volume 34, Issue 11, Pages 2274-2282, November 2012.
//
//
//===========================================================================
// Copyright (c) 2013 Radhakrishna Achanta.
//
// For commercial use please contact the author:
//
// Email: [email protected]
//===========================================================================

#if !defined(_SLIC_H_INCLUDED_)
#define _SLIC_H_INCLUDED_


#include 
#include 
#include 
using namespace std;


class SLIC  
{
public:
	SLIC();
	virtual ~SLIC();

	//============================================================================
	// Superpixel segmentation for a given number of superpixels
	//============================================================================
	void PerformSLICO_ForGivenK(
		const unsigned int*			ubuff,//Each 32 bit unsigned int contains ARGB pixel values.
		const int					width,
		const int					height,
		int*						klabels,
		int&						numlabels,
		const int&					K,
		const double&				m);

	//============================================================================
	// Save superpixel labels to pgm in raster scan order
	//============================================================================
	void SaveSuperpixelLabels2PPM(
		char*                       filename, 
		int *                       labels, 
		const int                   width, 
		const int                   height);

private:

	//============================================================================
	// Magic SLIC. No need to set M (compactness factor) and S (step size).
	// SLICO (SLIC Zero) varies only M dynamicaly, not S.
	//============================================================================
	void PerformSuperpixelSegmentation_VariableSandM(
		vector&				kseedsl,
		vector&				kseedsa,
		vector&				kseedsb,
		vector&				kseedsx,
		vector&				kseedsy,
		int*						klabels,
		const int&					STEP,
		const int&					NUMITR);

	//============================================================================
	// Pick seeds for superpixels when number of superpixels is input.
	//============================================================================
	void GetLABXYSeeds_ForGivenK(
		vector&				kseedsl,
		vector&				kseedsa,
		vector&				kseedsb,
		vector&				kseedsx,
		vector&				kseedsy,
		const int&					STEP,
		const bool&					perturbseeds,
		const vector&		edges);

	//============================================================================
	// Move the seeds to low gradient positions to avoid putting seeds at region boundaries.
	//============================================================================
	void PerturbSeeds(
		vector&				kseedsl,
		vector&				kseedsa,
		vector&				kseedsb,
		vector&				kseedsx,
		vector&				kseedsy,
		const vector&		edges);
	
	//============================================================================
	// Detect color edges, to help PerturbSeeds()
	//============================================================================
	void DetectLabEdges(
		const double*				lvec,
		const double*				avec,
		const double*				bvec,
		const int&					width,
		const int&					height,
		vector&				edges);
	
	//============================================================================
	// xRGB to XYZ conversion; helper for RGB2LAB()
	//============================================================================
	void RGB2XYZ(
		const int&					sR,
		const int&					sG,
		const int&					sB,
		double&						X,
		double&						Y,
		double&						Z);
	
	//============================================================================
	// sRGB to CIELAB conversion
	//============================================================================
	void RGB2LAB(
		const int&					sR,
		const int&					sG,
		const int&					sB,
		double&						lval,
		double&						aval,
		double&						bval);
	
	//============================================================================
	// sRGB to CIELAB conversion for 2-D images
	//============================================================================
	void DoRGBtoLABConversion(
		const unsigned int*&		ubuff,
		double*&					lvec,
		double*&					avec,
		double*&					bvec);

	//============================================================================
	// Post-processing of SLIC segmentation, to avoid stray labels.
	//============================================================================
	void EnforceLabelConnectivity(
		const int*					labels,
		const int&					width,
		const int&					height,
		int*						nlabels,//input labels that need to be corrected to remove stray labels
		int&						numlabels,//the number of labels changes in the end if segments are removed
		const int&					K); //the number of superpixels desired by the user

private:
	int										m_width;
	int										m_height;
	int										m_depth;

	double*									m_lvec;
	double*									m_avec;
	double*									m_bvec;

	double**								m_lvecvec;
	double**								m_avecvec;
	double**								m_bvecvec;
};

#endif // !defined(_SLIC_H_INCLUDED_)

运行结果:

并行计算 SLIC超像素算法(二) 代码分析_第4张图片

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