GDAL多光谱与全色图像融合简单使用

时间：2018-11-23 11:22:14 阅读：352 评论：0 收藏：0 [点我收藏+]

简述

最近在GDAL的代码中看见了gdalpansharpen.cpp，于是简单的尝试了一下。

融合后的效果比较差，这应该是我对这个算法的使用还不熟悉，还有些地方没有弄清楚。这个代码比较新，是2.1版本才加上的，我在看的时候，代码还有一些小问题，已经在github上提交了issuse了。

融合使用的数据是我在网上找到的高分一号的一景数据，先做了校正，形成全色波段TIFF(单波段)和多光谱波段TIFF(4波段)。

C++代码

代码基于当前https://github.com/OSGeo/gdal仓库的master分支构建。

// g++ gdal_pansharpen.cpp -o gdal_pansharpen -I../include -L../lib -lgdal

#include <gdalpansharpen.h>
#include <cpl_auto_close.h>
#include <cpl_error.h>

int main()
{
    GDALAllRegister();
    // 打开全色波段(高分辨率)文件
    GDALDatasetH hPanDset = GDALOpen("/mnt/data/GF1_PMS2_E116.5_N39.6_20130501_L1A0000127213-PAN2_rpc.tiff",GA_ReadOnly);
    CPL_AUTO_CLOSE_WARP(hPanDset,GDALClose);
    VALIDATE_POINTER1(hPanDset,"Open Pansharpen file failed",1);
    // 打开多光谱(低分辨率)文件
    GDALDatasetH hMssDset = GDALOpen("/mnt/data/GF1_PMS2_E116.5_N39.6_20130501_L1A0000127213-MSS2_rpc.tiff",GA_ReadOnly);
    CPL_AUTO_CLOSE_WARP(hMssDset,GDALClose);
    VALIDATE_POINTER1(hPanDset,"Open Spectral Band file failed",1);
    int nSpectralBands = GDALGetRasterCount(hMssDset);

    GDALPansharpenOptions opts;
    opts.ePansharpenAlg = GDAL_PSH_WEIGHTED_BROVEY;     // 超分辨率贝叶斯法,当前仅支持brovery加权
    opts.eResampleAlg    = GRIORA_Cubic;                 // 重采样至全色光谱波段分辨率的算法
    opts.nBitDepth           = 0;                            // 多光谱波段位深度，0表示默认
    opts.nWeightCount    = nSpectralBands;               // 权重系数数组元素个数(与输入多光谱波段数一致)
    double* pWeightCount= static_cast<double*>(
        CPLMalloc(opts.nWeightCount * sizeof(double))); // 权重系数数组
    CPL_AUTO_CLOSE_WARP(pWeightCount,CPLFree);
    opts.padfWeights = pWeightCount;
    opts.padfWeights[0] = 0.166;    // 蓝
    opts.padfWeights[1] = 0.167;    // 绿
    opts.padfWeights[2] = 0.167;    // 红
    opts.padfWeights[3] = 0.5;        // 近红外

    // 设置全色波段(高分辨率)
    opts.hPanchroBand = GDALGetRasterBand(hPanDset,1);
    // 设置多光谱波段
    opts.nInputSpectralBands = nSpectralBands;
    GDALRasterBandH* pInputSpectralBands = static_cast<GDALRasterBandH*>(
        CPLMalloc(sizeof(GDALRasterBandH) * nSpectralBands));
    CPL_AUTO_CLOSE_WARP(pInputSpectralBands,CPLFree);
    opts.pahInputSpectralBands = pInputSpectralBands;
    // std::generatr
    for(int i=0;i< nSpectralBands;++i) {
        opts.pahInputSpectralBands[i] = GDALGetRasterBand(hMssDset,i+1);
    }
    // 设置需要输出到全色波段分辨率的波段
    opts.nOutPansharpenedBands = 4;
    // 这个数组里面存的是pahInputSpectralBands里波段的索引值
    int panOutPansharpenedBands[4] = { 2, 1, 0, 3}; // 红、绿、蓝、近红外
    opts.panOutPansharpenedBands = panOutPansharpenedBands;

    opts.bHasNoData = FALSE;   // 全色和多光谱波段是否具有无效值(NoData值)
    opts.dfNoData   = 0.0;     // 全色和多光谱波段的无效值,也将作为输出的NoData值
    opts.nThreads   = -1;      // 使用的线程数，-1表示使用CPU线程数
    // 设置多光谱波段与全色波段在像素上的移位(保证地理空间位置对齐)
    // 都是相对于全色波段的0,0像素的像素(全色波段像素大小)偏移
    // 也就是两者的0,0像素的地理空间上的偏移量在全色波段分辨率相应的像素数
    double adfGTPan[6];
    GDALGetGeoTransform(hPanDset,adfGTPan);
    double adfGTMss[6];
    GDALGetGeoTransform(hPanDset,adfGTMss);
    opts.dfMSShiftX = (adfGTPan[0] - adfGTMss[0]) / adfGTPan[1];
    opts.dfMSShiftY = (adfGTPan[3] - adfGTMss[3]) / adfGTPan[5];

    GDALPansharpenOperation operation;
    CPLErr err = operation.Initialize(&opts);
    if(err != CE_None) {
        return -2;
    }
    // 创建输出文件(和全色波段一样大)
    int nOutXSize, nOutYSize;
    nOutXSize = GDALGetRasterBandXSize(opts.hPanchroBand);
    nOutYSize = GDALGetRasterBandYSize(opts.hPanchroBand);
    GDALDataType eBufDataType = GDALGetRasterDataType(opts.pahInputSpectralBands[0]);
    eBufDataType = GDT_Float64;
    GDALDriverH hDriver = GDALGetDriverByName("GTiff");
    CPLStringList CreateOption;
    CreateOption.AddNameValue("TILED", "YES");
    CreateOption.AddNameValue("BIGTIFF", "YES");
    CreateOption.AddNameValue("INTERLEAVE", "BAND");
    CreateOption.AddNameValue("COMPRESS", "LZW");   // 中度压缩
    CreateOption.AddNameValue("ZLEVEL", "6");

    GDALDatasetH hOutDset = GDALCreate(hDriver,
                "/mnt/data/GF1_PMS2_E116.5_N39.6_20130501_L1A0000127213.tif",
                nOutXSize, nOutYSize, nSpectralBands, GDT_UInt16,
                CreateOption);
    CPL_AUTO_CLOSE_WARP(hOutDset,GDALClose);
    VALIDATE_POINTER1(hOutDset,"Create Output file error", -3);

    GDALSetGeoTransform(hOutDset, adfGTPan);
    GDALSetProjection(hOutDset,GDALGetProjectionRef(hPanDset));

     void* pData = CPLMalloc(256*256*GDALGetDataTypeSizeBytes(eBufDataType)*nSpectralBands);
     CPL_AUTO_CLOSE_WARP(pData,CPLFree);

    for(int nYOff = 0; nYOff < nOutYSize; nYOff += 256) {
        for(int nXOff = 0; nXOff < nOutXSize; nXOff += 256) {
            int nXSize = std::min(nOutXSize - nXOff,256);
            int nYSize = std::min(nOutYSize - nYOff,256);
            printf("Process[%6d,%6d,%6d,%6d]\r",nXOff,nYOff,nXOff+nXSize,nYOff+nYSize);

            err = operation.ProcessRegion(nXOff,nYOff,nXSize,nYSize,pData,eBufDataType);
            if(err == CE_Failure) {
                CPLError(err,CPLE_AppDefined,"operation.ProcessRegion");
                return -4;
            }
            int panBandMap[4] = { 1, 2, 3, 4};
            err = GDALDatasetRasterIO(hOutDset, GF_Write,
                        nXOff,nYOff,nXSize,nYSize,
                        pData,nXSize,nYSize,
                        eBufDataType,
                        4,panBandMap,
                        0,0,nXSize*nYSize*GDALGetDataTypeSizeBytes(eBufDataType));
        }
    }
    puts("\nPansharpen finished");

    return 0;
}