灰度共生矩阵求得的熵、能量的值很奇怪

Question

熵：-5.72232e+006，能量：2.73135e+009
怎么感觉数据值很大，新手也不知哪里有问题，求问，十分感谢

#define GLCM_DIS 3 //灰度共生矩阵的统计距离

#define GLCM_CLASS 16 //计算灰度共生矩阵的图像灰度值等级化

#define GLCM_ANGLE_HORIZATION 0 //水平

#define GLCM_ANGLE_VERTICAL 1 //垂直

#define GLCM_ANGLE_DIGONAL 2 //对角

//int calGLCM(IplImage* bWavelet,int angleDirection,double* featureVector)

int calGLCM(Mat& bWavelet,int angleDirection,double* featureVector)

{

int i,j;

int width,height;

    if(bWavelet.empty() )  
        return 1;  

    width = bWavelet.cols;  
    height = bWavelet.rows;  

    int * glcm = new int[GLCM_CLASS * GLCM_CLASS];  
    int * histImage = new int[width * height];  

    if(NULL == glcm || NULL == histImage)  
        return 2;  

    //灰度等级化---分GLCM_CLASS个等级  

    for(i = 0;i < height;i++){  
        uchar *data =bWavelet.ptr<uchar>(i);  
        for(j = 0;j < width;j++){  
            histImage[i * width + j] = (int)(data[j] * GLCM_CLASS /256);  
        }  
    }  

    //初始化共生矩阵  
    for (i = 0;i < GLCM_CLASS;i++)  
        for (j = 0;j < GLCM_CLASS;j++)  
            glcm[i * GLCM_CLASS + j] = 0;  

    //计算灰度共生矩阵  
    int w,k,l;  
    //水平方向  
    if(angleDirection == GLCM_ANGLE_HORIZATION)  
    {  
        for (i = 0;i < height;i++)  
        {  
            for (j = 0;j < width;j++)  
            {  
                l = histImage[i * width + j];  
                if(j + GLCM_DIS >= 0 && j + GLCM_DIS < width)  
                {  
                    k = histImage[i * width + j + GLCM_DIS];  
                    glcm[l * GLCM_CLASS + k]++;  
                }  
                if(j - GLCM_DIS >= 0 && j - GLCM_DIS < width)  
                {  
                    k = histImage[i * width + j - GLCM_DIS];  
                    glcm[l * GLCM_CLASS + k]++;  
                }  
            }  
        }  
    }  
    //垂直方向  
    else if(angleDirection == GLCM_ANGLE_VERTICAL)  
    {  
        for (i = 0;i < height;i++)  
        {  
            for (j = 0;j < width;j++)  
            {  
                l = histImage[i * width + j];  
                if(i + GLCM_DIS >= 0 && i + GLCM_DIS < height)   
                {  
                    k = histImage[(i + GLCM_DIS) * width + j];  
                    glcm[l * GLCM_CLASS + k]++;  
                }  
                if(i - GLCM_DIS >= 0 && i - GLCM_DIS < height)   
                {  
                    k = histImage[(i - GLCM_DIS) * width + j];  
                    glcm[l * GLCM_CLASS + k]++;  
                }  
            }  
        }  
    }  
    //对角方向  
    else if(angleDirection == GLCM_ANGLE_DIGONAL)  
    {  
        for (i = 0;i < height;i++)  
        {  
            for (j = 0;j < width;j++)  
            {  
                l = histImage[i * width + j];  

                if(j + GLCM_DIS >= 0 && j + GLCM_DIS < width && i + GLCM_DIS >= 0 && i + GLCM_DIS < height)  
                {  
                    k = histImage[(i + GLCM_DIS) * width + j + GLCM_DIS];  
                    glcm[l * GLCM_CLASS + k]++;  
                }  
                if(j - GLCM_DIS >= 0 && j - GLCM_DIS < width && i - GLCM_DIS >= 0 && i - GLCM_DIS < height)  
                {  
                    k = histImage[(i - GLCM_DIS) * width + j - GLCM_DIS];  
                    glcm[l * GLCM_CLASS + k]++;  
                }  
            }  
        }  
    }  

    //计算特征值  
    double entropy = 0,energy = 0,contrast = 0,homogenity = 0;  
    for (i = 0;i < GLCM_CLASS;i++)  
    {  
        for (j = 0;j < GLCM_CLASS;j++)  
        {  
            //if(i==j&&i==10)cout<<glcm[i * GLCM_CLASS + j]<<endl;
            //熵  
            if(glcm[i * GLCM_CLASS + j] > 0)  
                entropy -= glcm[i * GLCM_CLASS + j] * log10(double(glcm[i * GLCM_CLASS + j]));  
            //能量  
            energy += glcm[i * GLCM_CLASS + j] * glcm[i * GLCM_CLASS + j];  
            //对比度  
            contrast += (i - j) * (i - j) * glcm[i * GLCM_CLASS + j];  
            //一致性  
            homogenity += 1.0 / (1 + (i - j) * (i - j)) * glcm[i * GLCM_CLASS + j];  
        }  
    }  
    //返回特征值  
    i = 0;  
    featureVector[i++] = entropy;  
    featureVector[i++] = energy;  
    featureVector[i++] = contrast;  
    featureVector[i++] = homogenity;  
  cout<<entropy<<","<<energy<<","<<endl;
    delete[] glcm;  
    delete[] histImage;  
    return 0;  
}  

Answer 1

计算结果

用的代码跟你一样，可能是因为图片不同吧