图像转铅笔素描

Introduce

       最近看了一篇论文《Combining Sketch and Tone for Pencil Drawing Production》，感觉很好玩，所以就想实现了一下，但是里面有些公式是在太难理解了，我就在github上找到了一份代码，对其进行了重构。

方法介绍

       这篇论文中前面形成stroke structure还是比较好理解的，流程如下：

1）计算图像的梯度图像；

2）用8个核对梯度图像进行卷积，每个核为指向各个方向的直线，共形成8张卷积图像（卷积）；

3）比较8张卷积图像，对应像素位置的值最大则保留，于是又形成8张图像（筛选）；

4）对3）中形成的8张图像，进行卷积，卷积核为每张图像对应的卷积图像的生成核（强化）；

5）将4）生成的8张图像相加，并规范化。

        后面形成tone map，以及进行texture rendering包含一些固定参数，不容易推到出合适的，作者给出了一些推荐值，还有一些解公式之类的工作，这里无法叙述，可参详http://www.cnblogs.com/Imageshop/p/4285566.html 。

效果图

       生成效果图如下：

  

        两张图像对比还是前一张香蕉的图像更好看，观察了多张图片，我个人认为画面内容简单生成的图像更好看。

代码    

       除了前面部分是理解后实现的，其余代码大部分是重构，原始代码是https://github.com/HVisionSensing/PicWall，我的代码如下：

#include <stdio.h>#include <opencv2/core/core.hpp>#include <opencv2/imgproc/imgproc.hpp>#include <opencv2/highgui/highgui.hpp>//#define DEBUG_INFOvoid generate_conv_kernel(int ksize, float angle, int hardness, cv::Mat &kernel){    int halfSize = ksize / 2;    int size = halfSize * 2 - 1;    int y0 = halfSize - hardness + 1;    int y1 = halfSize + hardness - 1;    cv::Mat rect, rotateMat;    cv::Point2i central;    kernel = cv::Mat(size, size, CV_32FC1, cv::Scalar(0));    rect = cv::Mat(kernel, cv::Rect(0, y0, size, y1 - y0 + 1));    rect = cv::Scalar(255);    central = cv::Point2i(halfSize, halfSize);    rotateMat = cv::getRotationMatrix2D(central, angle, 1.0);    cv::warpAffine(kernel, kernel, rotateMat, kernel.size());}void generate_stroke_structure(cv::Mat &gray, int hardness, int directions, float strength, cv::Mat &structure){    cv::Mat gradient;    cv::Mat *kernels = new cv::Mat[directions];    cv::Mat *Gs = new cv::Mat[directions];    cv::Mat *Cs = new cv::Mat[directions];    int rows, cols;    int ksize;    assert(gray.depth() == CV_32F);    rows = gray.rows;    cols = gray.cols;    {        cv::Mat gx, gy;        cv::Sobel(gray, gx, CV_32FC1, 1, 0);        cv::Sobel(gray, gy, CV_32FC1, 0, 1);        cv::magnitude(gx, gy, gradient);#ifdef DEBUG_INFO        cv::imshow("gradient", gradient/255);        cv::waitKey();#endif    }    ksize = (rows < cols ? rows : cols) / 30;    for(int i = 0; i < directions; i++)    {        float angle = i * 180.0 / directions;        generate_conv_kernel(ksize, angle, hardness, kernels[i]);        cv::filter2D(gradient, Gs[i], -1, kernels[i]);        Cs[i] = cv::Mat(rows, cols, CV_32FC1, cv::Scalar(0));    }    for(int y = 0; y < rows; y++)    {        for(int x = 0; x < cols; x++)        {            int idx = 0;            float mmax = 0, t;            for(int i = 0; i < directions; i++)            {                if( (t = Gs[i].at<float>(y, x)) > mmax)                {                    mmax = t;                    idx = i;                }            }            Cs[idx].at<float>(y, x) = gradient.at<float>(y, x);        }    }    structure = cv::Mat(rows, cols, CV_32FC1, cv::Scalar(0));    for(int i = 0; i < directions; i++)    {        cv::filter2D(Cs[i], Cs[i], -1, kernels[i]);        structure += Cs[i];    }    cv::normalize(structure, structure, 0, 1, cv::NORM_MINMAX);    structure = 1 - structure * strength;    delete[] kernels;    delete[] Gs;    delete[] Cs;}void calc_hist(uchar *data, int width, int height, int stride, float hist[]){    float sq = width * height;    memset(hist, 0, sizeof(float) * 256);    for(int y = 0; y < height; y++)    {        for(int x = 0; x < width; x++)            hist[data[x]] ++;        data += stride;    }    for(int i = 0; i < 256; i++)        hist[i] /= sq;}void specific_hist(float *hist, float *target, float histMap[]){    float cumHist[256], dist[256 * 256], *ptr;    int start = 0, end = 0, lastStart = 0, lastEnd = 0;    cumHist[0] = hist[0];    for(int i = 1; i < 256; i++)        cumHist[i] = cumHist[i-1] + hist[i];    ptr = dist;    for(int y = 0; y < 256; y++)    {        for(int x = 0; x < 256; x++)            ptr[x] = fabs(cumHist[x] - target[y]);        ptr += 256;    }    ptr = dist;    for(int y = 0; y < 256; y++)    {        float mmin = ptr[0];        for(int x = 1; x < 256; x++)        {            if(mmin >= ptr[x])            {                mmin = ptr[x];                end = x;            }        }        if(start != lastStart || end != lastEnd)        {            for(int x = start; x <= end; x++)                histMap[x] = y;            lastStart = start;            lastEnd = end;            start = end + 1;        }        ptr += 256;    }}void generate_tone(cv::Mat &gray, float hist[], cv::Mat &tone){    float target[256], bright[256], dark[256], mid[256];    float sumB = 0, sumD = 0, sumM = 0, sum = 0;    int rows = gray.rows;    int cols = gray.cols;    tone = cv::Mat(rows, cols, CV_32FC1, cv::Scalar(0));    for(int i = 0; i < 256; i++)    {        bright[i] = expf((i - 255.0) / 9);        dark[i] = expf( (i - 90) * (i - 90) / -242.0);        sumB += bright[i];        sumD += dark[i];        if( 105 <= i && i <= 225)            mid[i] = 1;        else            mid[i] = 0;        sumM += mid[i];    }    sum = 0;    for(int i = 0; i < 256; i++)    {        float b = bright[i] / sumB;        float d = dark[i] / sumD;        float m = mid[i] / sumM;        sum +=  (52 * b + 37 * m + 11 * d) / 100;        target[i] = sum;    }    {        float histMap[256];        specific_hist(hist, target, histMap);        for(int y = 0; y < rows; y++)        {            float *ptr1 = (float*)(gray.data + gray.step * y);            float *ptr2 = (float*)(tone.data + tone.step * y);            for(int x = 0; x < cols; x++)                ptr2[x] = histMap[(int)ptr1[x]] / 255.0;        }    }}void texture_rendering(cv::Mat &tone, cv::Mat &image,  cv::Mat &texture){    int rows = tone.rows;    int cols = tone.cols;    int ny = ceil(float(rows) / image.rows);    int nx = ceil(float(cols) / image.cols);    cv::Mat beta(rows, cols, CV_32FC1, cv::Scalar(1));    assert(tone.depth() == CV_32F && image.depth() == CV_32F);    texture = cv::Mat(rows, cols, CV_32FC1, cv::Scalar(0));    if(ny > 1 || nx > 1)        cv::repeat(image, ny, nx, image);    cv::resize(image, image, cv::Size(cols, rows));    image /= 255;    for(int x = 0; x < cols; x++)        beta.at<float>(0, x) = logf(tone.at<float>(0, x) + FLT_EPSILON) /            logf(image.at<float>(0, x) + FLT_EPSILON);    for(int y = 0; y < rows; y++)        beta.at<float>(y, 0) = logf(tone.at<float>(y, 0) + FLT_EPSILON) /            logf(image.at<float>(y, 0) + FLT_EPSILON);    for(int y = 1; y < rows; y++)    {        for(int x = 1; x < cols; x++)        {            float t = logf(image.at<float>(y, x) + FLT_EPSILON);            float v = (t * logf(tone.at<float>(y, x) + FLT_EPSILON) +                    0.2 * ( beta.at<float>(y-1, x) + beta.at<float>(y, x - 1) )) / (t * t + 0.4);            beta.at<float>(y, x) = v;        }    }#ifdef DEBUG_INFO    cv::imshow("beta", beta);    cv::waitKey();#endif    for(int y = 0; y < rows; y++)        for(int x = 0; x < cols; x++)            texture.at<float>(y, x) = powf(image.at<float>(y, x), beta.at<float>(y, x));}void generate_sketch_images(cv::Mat &img, cv::Mat &pencilSketch, cv::Mat &colorSketch){    assert(img.channels() == 3);    cv::Mat gray, structure, tone, texture;    cv::cvtColor(img, gray, cv::COLOR_BGR2GRAY);    float hist[256];    calc_hist(gray.data, gray.cols, gray.rows, gray.step, hist);    gray.convertTo(gray, CV_32FC1);    generate_stroke_structure(gray, 1, 8, 0.9, structure);#ifdef DEBUG_INFO    cv::imshow("structure", structure);    cv::waitKey();#endif    generate_tone(gray, hist, tone);#ifdef DEBUG_INFO    cv::imshow("tone", tone);    cv::waitKey();#endif    texture_rendering(tone, gray, texture);#ifdef DEBUG_INFO    cv::imshow("texture", texture);    cv::waitKey();#endif    pencilSketch = structure.mul(texture) * 255;    pencilSketch.convertTo(pencilSketch, CV_8UC1);#ifdef DEBUG_INFO    cv::imshow("pencil", pencilSketch);    cv::waitKey();#endif    {        cv::Mat labImg;        std::vector<cv::Mat> channels;        cv::cvtColor(img, labImg, cv::COLOR_BGR2Lab);        cv::split(labImg, channels);        channels[0] = pencilSketch;        cv::merge(channels, labImg);        cv::cvtColor(labImg, colorSketch, cv::COLOR_Lab2BGR);    }#ifdef DEBUG_INFO    cv::imshow("color", colorSketch);    cv::waitKey();#endif}int main(int argc, char **argv){    if(argc < 4)    {        printf("Usage: %s [input image] [output pencil image] [output color pencil image]\n", argv[0]);        return 1;    }    cv::Mat img = cv::imread(argv[1], CV_LOAD_IMAGE_COLOR);    cv::Mat pencil, colorPencil;    generate_sketch_images(img, pencil, colorPencil);    cv::imshow("pencil", pencil);    cv::imshow("color pencil", colorPencil);    cv::waitKey();    if(!cv::imwrite(argv[2], pencil))    {        printf("Can't write image %s\n", argv[2]);        return 2;    }    if(! cv::imwrite(argv[3], colorPencil))    {        printf("Can't write image %s\n", argv[3]);        return 3;    }    return 0;}