hugin_hdrmerge.cpp

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// -*- c-basic-offset: 4 -*-

#include <hugin_config.h>
#include <hugin_version.h>

#include <fstream>
#include <sstream>
#include <cmath>
#include <algorithm>

#include <boost/shared_ptr.hpp>

#include <vigra/error.hxx>
#include <vigra/functorexpression.hxx>
#include <vigra_impex/codecmanager.hxx>

#include <hugin_utils/utils.h>

#include <vigra_ext/impexalpha.hxx>
#include <vigra_ext/HDRUtils.h>
#include <vigra_ext/ReduceOpenEXR.h>

//#include <PT/PTOptimise.h>

#ifdef WIN32
 #include <getopt.h>
#else
 #include <unistd.h>
#endif

#include "../deghosting/deghosting.h"
#include "../deghosting/khan.h"

using namespace std;

using namespace hugin_utils;
using namespace vigra;
using namespace vigra::functor;
using namespace vigra_ext;

using namespace deghosting;

// define the types of images we will use.
// use float for RGB
typedef vigra::FRGBImage ImageType;

// smart pointers to the images.
typedef boost::shared_ptr<ImageType> ImagePtr;
//typedef boost::shared_ptr<vigra::BImage> BImagePtr;

static int g_verbose = 0;

const uint16_t OTHER_GRAY = 1;

// load all images and apply a weighted average merge, with
// special cases for completely over or underexposed pixels.
bool mergeWeightedAverage(vector<string> inputFiles, FRGBImage & output)
{
    // load all images into memory
    vector<ImagePtr> images;
    vector<BImagePtr> weightImages;

    for (size_t i=0; i < inputFiles.size(); i++)
    {
        ImagePtr img = ImagePtr(new ImageType());
        BImagePtr weight = BImagePtr(new BImage());

        if (g_verbose > 0) {
            std::cout << "Loading image: " << inputFiles[i] << std::endl;
        }
        vigra::ImageImportInfo info(inputFiles[i].c_str());
        img->resize(info.size());
        weight->resize(info.size());
        if (info.numBands() == 4) {
            importImageAlpha(info, destImage(*img), destImage(*weight));
        } else {
            importImage(info, destImage(*img));
        }
        images.push_back(img);
        weightImages.push_back(weight);
    }

    // ensure all images have the same size (cropped images not supported yet)
    int width=images[0]->width();
    int height=images[0]->height();
    for (unsigned i=1; i < images.size(); i++) {
        if (images[i]->width() != width || images[i]->height() != height) {
            std::cerr << "Error: Input images need to be of the same size" << std::endl;
            return false;
        }
    }
    output.resize(width,height);
    if (g_verbose > 0) {
        std::cout << "Calculating weighted average " << std::endl;
    }
    // apply weighted average functor with
    // heuristic to deal with pixels that are overexposed in all images
    ReduceToHDRFunctor<ImageType::value_type> waverage;

    // loop over all pixels in the image (very low level access)
    for (int y=0; y < height; y++) {
        for (int x=0; x < width; x++) {
            waverage.reset();
            // loop over all exposures
            for (unsigned imgNr=0; imgNr < images.size(); imgNr++) {
                // add pixel to weighted average
                waverage( (*images[imgNr])(x,y), (*weightImages[imgNr])(x,y) );
            }
            // get result
            output(x,y) = waverage();
        }
    }
    return true;
}

bool weightedAverageOfImageFiles(const vector<string> &inputFiles,
                                    const vector<FImagePtr> &weights,
                                    FRGBImage &output)
{
    if(g_verbose > 0) {
        cout << "Merging input images" << endl;
    }
    int width = (weights[0])->width();
    int height = (weights[0])->height();
    
    assert(inputFiles.size() == weights.size());
    
    BasicImage<NumericTraits<FRGBImage::PixelType>::Promote> weightedImg(width, height);
    BasicImage<NumericTraits<FImage::PixelType>::Promote> weightAdded(width, height);
    for(unsigned i = 0; i < inputFiles.size(); i++) {
        ImageImportInfo inputInfo(inputFiles[i].c_str());
        BasicImage<NumericTraits<FRGBImage::PixelType>::Promote> tmpImg(inputInfo.size());
        
        //load image
        if (inputInfo.numBands() == 4) {
            BImage tmpMask(inputInfo.size());
            importImageAlpha(inputInfo, destImage(tmpImg), destImage(tmpMask));
        } else {
            importImage(inputInfo, destImage(tmpImg));
        }
        
        //combine with weight
        combineTwoImages(srcImageRange(tmpImg), srcImage(*(weights[i])), destImage(tmpImg), Arg1() * Arg2());
        
        combineTwoImages(srcImageRange(tmpImg), srcImage(weightedImg), destImage(weightedImg), Arg1() + Arg2());
        
        combineTwoImages(srcImageRange(weightAdded), srcImage(*(weights[i])), destImage(weightAdded), Arg1() + Arg2());
    }
    output.resize(width, height);
    combineTwoImages(srcImageRange(weightedImg), srcImage(weightAdded), destImage(output), Arg1() / Arg2());
    
    return true;
}

static void usage(const char * name)
{
    cerr << name << ": merge overlapping images" << std::endl
         << std::endl
         << "hugin_hdrmerge version " << DISPLAY_VERSION << std::endl
         << std::endl
         << "Usage: " << name  << " [options] -o output.exr <input-files>" << std::endl
         << "Valid options are:" << std::endl
         << "  -o prefix output file" << std::endl
         << "  -m mode   merge mode, can be one of: avg (default), avg_slow, khan, if avg, no" << std::endl
         << "            -i and -s options apply" << std::endl
         << "  -i iter   number of iterations to execute (default is 4). Khan only" << std::endl
         << "  -s sigma  standard deviation of Gaussian weighting" << endl
         << "            function (sigma > 0); default: 30. Khan only" << endl
         << "  -a set    advanced settings. Possible options are:" << endl
         << "              f   use gray images for computation. It's about two times faster" << endl
         << "                  but it usually returns worse results." << endl
         << "              g   use gamma 2.2 correction instead of logarithm" << endl
         << "              m   do not scale image, NOTE: slows down process" << endl
         << "  -c        Only consider pixels that are defined in all images (avg mode only)" << std::endl
         << "  -v        Verbose, print progress messages, repeat for" << std::endl
         << "            even more verbose output" << std::endl
         << "  -h        Display help (this text)" << std::endl
         << std::endl;
}


int main(int argc, char *argv[])
{

    // parse arguments
    const char * optstring = "chvo:m:i:s:a:el";
    int c;

    opterr = 0;

    g_verbose = 0;
    std::string outputFile = "merged.exr";
    std::string mode = "avg";
    bool onlyCompleteOverlap = false;
    int iterations = 4;
    double sigma = 30;
    uint16_t flags = 0;
    uint16_t otherFlags = 0;
    

    string basename;
    while ((c = getopt (argc, argv, optstring)) != -1) {
        switch (c) {
        case 'm':
            mode = optarg;
            break;
        case 'i':
            iterations = atoi(optarg);
            break;
        case 's':
            sigma = atof(optarg);
            break;
        case 'a':
            for(char *c = optarg; *c; c++) {
                switch(*c) {
                    case 'f':
                        otherFlags += OTHER_GRAY;
                        break;
                    case 'g':
                        flags += ADV_GAMMA;
                        break;
                    case 'm':
                        flags -= ADV_MULTIRES;
                        break;
                    default:
                        cerr<< "Error: unknown option" << endl;
                        exit(1);
                }
            }
        case 'c':
            onlyCompleteOverlap = true;
            break;
       case 'o':
            outputFile = optarg;
            break;
        case 'v':
            g_verbose++;
            break;
        case 'h':
            usage(argv[0]);
            return 0;
        default:
            cerr << "Invalid parameter: " << optarg << std::endl;
            usage(argv[0]);
            return 1;
        }
    }//end while

    unsigned nFiles = argc - optind;
    if (nFiles == 0) {
        std::cerr << std::endl << "Error: at least one input image needed" << std::endl <<std::endl;
        usage(argv[0]);
        return 1;
    } else if (nFiles == 1) {
        std::cout << std::endl << "Only one input image given. Copying input image to output image." << std::endl;
        // simply copy image file
        std::ifstream infile(argv[optind], std::ios_base::binary);
        std::ofstream outfile(outputFile.c_str(), std::ios_base::binary);
        outfile << infile.rdbuf();
        return 0;
    }

    // load all images
    vector<string> inputFiles;
    for (size_t i=optind; i < (size_t)argc; i++)
    {
        inputFiles.push_back(argv[i]);
    }

    // output image
    ImageType output;
    try {
        if (mode == "avg_slow") {
            // use a weighted average, with special consideration of pixels
            // that are completely over or underexposed in all exposures.
            if (g_verbose > 0) {
                cout << "Running simple weighted avg algorithm" << std::endl;
            }

            mergeWeightedAverage(inputFiles, output);
            // save output file
            if (g_verbose > 0) {
                std::cout << "Writing " << outputFile << std::endl;
            }
            ImageExportInfo exinfo(outputFile.c_str());
            exinfo.setPixelType("FLOAT");
            BImage alpha(output.width(), output.height(), 255);
            exportImageAlpha(srcImageRange(output), srcImage(alpha), exinfo);
        } else if (mode == "avg") {
            // apply weighted average functor with
            // heuristic to deal with pixels that are overexposed in all images
            ReduceToHDRFunctor<ImageType::value_type> waverage;
            // calc weighted average without loading the whole images into memory
            reduceFilesToHDR(inputFiles, outputFile, onlyCompleteOverlap, waverage);
        } else if (mode == "khan") {
            Deghosting* deghoster = NULL;
            vector<FImagePtr> weights;
            
            if (otherFlags & OTHER_GRAY) {
                Khan<float> khanDeghoster(inputFiles, flags, 0, iterations, sigma, g_verbose);
                deghoster = &khanDeghoster;
                weights = deghoster->createWeightMasks();
            } else {
                Khan<RGBValue<float> > khanDeghoster(inputFiles, flags, 0, iterations, sigma, g_verbose);
                deghoster = &khanDeghoster;
                weights = deghoster->createWeightMasks();
            }
                        
            weightedAverageOfImageFiles(inputFiles, weights, output);
            if (g_verbose > 0) {
                std::cout << "Writing " << outputFile << std::endl;
            }
            ImageExportInfo exinfo(outputFile.c_str());
            exinfo.setPixelType("FLOAT");
            BImage alpha(output.width(), output.height(), 255);
            exportImageAlpha(srcImageRange(output), srcImage(alpha), exinfo);
        } else {
            std::cerr << "Unknown merge mode, see help for a list of possible modes" << std::endl;
            return 1;
        }
    } catch (std::exception & e) {
        cerr << "caught exception: " << e.what() << std::endl;
        abort();
    }

    return 0;
}

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