public StereoCorrespondence()
{
// cvFindStereoCorrespondenceBM + cvFindStereoCorrespondenceGC
// ブロックマッチング, グラフカットの両アルゴリズムによるステレオマッチング
// 入力画像の読み込み
using (IplImage imgLeft = new IplImage(Const.ImageTsukubaLeft, LoadMode.GrayScale))
using (IplImage imgRight = new IplImage(Const.ImageTsukubaRight, LoadMode.GrayScale))
{
// 視差画像, 出力画像の領域を確保
using (IplImage dispBM = new IplImage(imgLeft.Size, BitDepth.S16, 1))
using (IplImage dispLeft = new IplImage(imgLeft.Size, BitDepth.S16, 1))
using (IplImage dispRight = new IplImage(imgLeft.Size, BitDepth.S16, 1))
using (IplImage dstBM = new IplImage(imgLeft.Size, BitDepth.U8, 1))
using (IplImage dstGC = new IplImage(imgLeft.Size, BitDepth.U8, 1))
using (IplImage dstAux = new IplImage(imgLeft.Size, BitDepth.U8, 1))
using (Mat dstSGBM = new Mat())
{
// 距離計測とスケーリング
int sad = 3;
using (CvStereoBMState stateBM = new CvStereoBMState(StereoBMPreset.Basic, 16))
using (CvStereoGCState stateGC = new CvStereoGCState(16, 2))
using (StereoSGBM sgbm = new StereoSGBM()
{
MinDisparity = 0,
NumberOfDisparities = 32,
PreFilterCap = 63,
SADWindowSize = sad,
P1 = 8 * imgLeft.NChannels * sad * sad,
P2 = 32 * imgLeft.NChannels * sad * sad,
UniquenessRatio = 10,
SpeckleWindowSize = 100,
SpeckleRange = 32,
Disp12MaxDiff = 1,
FullDP = false,
})
{
Cv.FindStereoCorrespondenceBM(imgLeft, imgRight, dispBM, stateBM); // stateBM.FindStereoCorrespondence(imgLeft, imgRight, dispBM);
Cv.FindStereoCorrespondenceGC(imgLeft, imgRight, dispLeft, dispRight, stateGC, false); // stateGC.FindStereoCorrespondence(imgLeft, imgRight, dispLeft, dispRight, false);
Cv.FindStereoCorrespondence(imgLeft, imgRight, DisparityMode.Birchfield, dstAux, 50, 25, 5, 12, 15, 25);
sgbm.FindCorrespondence(new Mat(imgLeft), new Mat(imgRight), dstSGBM);
Cv.ConvertScale(dispBM, dstBM, 1);
Cv.ConvertScale(dispLeft, dstGC, -16);
Cv.ConvertScale(dstAux, dstAux, 16);
dstSGBM.ConvertTo(dstSGBM, dstSGBM.Type, 32, 0);
using (new CvWindow("Stereo Correspondence (BM)", dstBM))
using (new CvWindow("Stereo Correspondence (GC)", dstGC))
using (new CvWindow("Stereo Correspondence (cvaux)", dstAux))
using (new CvWindow("Stereo Correspondence (SGBM)", dstSGBM.ToIplImage()))
{
Cv.WaitKey();
}
}
}
}
}
public void Run()
{
// Load left&right images
using (var imgLeft = new IplImage(FilePath.Image.TsukubaLeft, LoadMode.GrayScale))
using (var imgRight = new IplImage(FilePath.Image.TsukubaRight, LoadMode.GrayScale))
{
// output image buffers
using (var dispBM = new IplImage(imgLeft.Size, BitDepth.S16, 1))
using (var dispLeft = new IplImage(imgLeft.Size, BitDepth.S16, 1))
using (var dispRight = new IplImage(imgLeft.Size, BitDepth.S16, 1))
using (var dstBM = new IplImage(imgLeft.Size, BitDepth.U8, 1))
using (var dstGC = new IplImage(imgLeft.Size, BitDepth.U8, 1))
using (var dstAux = new IplImage(imgLeft.Size, BitDepth.U8, 1))
using (var dstSGBM = new Mat())
{
// measures distance and scales
const int sad = 3;
using (var stateBM = new CvStereoBMState(StereoBMPreset.Basic, 16))
using (var stateGC = new CvStereoGCState(16, 2))
using (var sgbm = new StereoSGBM() // C++
{
MinDisparity = 0,
NumberOfDisparities = 32,
PreFilterCap = 63,
SADWindowSize = sad,
P1 = 8 * imgLeft.NChannels * sad * sad,
P2 = 32 * imgLeft.NChannels * sad * sad,
UniquenessRatio = 10,
SpeckleWindowSize = 100,
SpeckleRange = 32,
Disp12MaxDiff = 1,
FullDP = false,
})
{
Cv.FindStereoCorrespondenceBM(imgLeft, imgRight, dispBM, stateBM);
Cv.FindStereoCorrespondenceGC(imgLeft, imgRight, dispLeft, dispRight, stateGC, false);
Cv.FindStereoCorrespondence(imgLeft, imgRight, DisparityMode.Birchfield, dstAux, 50, 25, 5, 12, 15, 25); // cvaux
sgbm.Compute(new Mat(imgLeft), new Mat(imgRight), dstSGBM);
Cv.ConvertScale(dispBM, dstBM, 1);
Cv.ConvertScale(dispLeft, dstGC, -16);
Cv.ConvertScale(dstAux, dstAux, 16);
dstSGBM.ConvertTo(dstSGBM, dstSGBM.Type(), 32, 0);
using (new CvWindow("Stereo Correspondence (BM)", dstBM))
using (new CvWindow("Stereo Correspondence (GC)", dstGC))
using (new CvWindow("Stereo Correspondence (cvaux)", dstAux))
using (new CvWindow("Stereo Correspondence (SGBM)", dstSGBM.ToIplImage()))
{
Cv.WaitKey();
}
}
}
}
}
/// <summary>
/// グラフカットに基づくアルゴリズムにより視差画像を計算する
/// </summary>
/// <param name="left">左画像．シングルチャンネル，8ビット．</param>
/// <param name="right">右画像．左画像と同じサイズ，同じ種類．</param>
/// <param name="dispLeft">出力オプション：シングルチャンネル，16ビット，符号有り整数．入力画像と同じサイズの左視差画像． </param>
/// <param name="dispRight">出力オプション：シングルチャンネル，16ビット，符号有り整数．入力画像と同じサイズの右視差画像． </param>
/// <param name="state">ステレオマッチング構造体．</param>
/// <param name="useDisparityGuess">このパラメータが 0 でない場合， あらかじめ定義された視差画像を用いて計算が開始される．つまり， dispLeft と dispRight が共に，妥当な視差画像である必要がある． そうでない場合は，（すべてのピクセルがオクルージョンとなっている）空の視差画像から開始される．</param>
#else
/// <summary>
/// Computes the disparity map using graph cut-based algorithm
/// </summary>
/// <param name="left">The left single-channel, 8-bit image. </param>
/// <param name="right">The right image of the same size and the same type. </param>
/// <param name="dispLeft">The optional output single-channel 16-bit signed left disparity map of the same size as input images. </param>
/// <param name="dispRight">The optional output single-channel 16-bit signed right disparity map of the same size as input images. </param>
/// <param name="state">Stereo correspondence structure. </param>
/// <param name="useDisparityGuess">If the parameter is not zero, the algorithm will start with pre-defined disparity maps. Both dispLeft and dispRight should be valid disparity maps. Otherwise, the function starts with blank disparity maps (all pixels are marked as occlusions). </param>
#endif
public static void FindStereoCorrespondenceGC(CvArr left, CvArr right, CvArr dispLeft, CvArr dispRight, CvStereoGCState state, bool useDisparityGuess)
{
if (left == null)
throw new ArgumentNullException("left");
if (right == null)
throw new ArgumentNullException("right");
if (dispLeft == null)
throw new ArgumentNullException("dispLeft");
if (dispRight == null)
throw new ArgumentNullException("dispRight");
if (state == null)
throw new ArgumentNullException("state");
NativeMethods.cvFindStereoCorrespondenceGC(left.CvPtr, right.CvPtr, dispLeft.CvPtr, dispRight.CvPtr, state.CvPtr, useDisparityGuess);
}
// ReSharper restore InconsistentNaming
#endregion
#region FindStereoCorrespondenceGC
// ReSharper disable InconsistentNaming
#if LANG_JP
/// <summary>
/// グラフカットに基づくアルゴリズムにより視差画像を計算する
/// </summary>
/// <param name="left">左画像．シングルチャンネル，8ビット．</param>
/// <param name="right">右画像．左画像と同じサイズ，同じ種類．</param>
/// <param name="dispLeft">出力オプション：シングルチャンネル，16ビット，符号有り整数．入力画像と同じサイズの左視差画像． </param>
/// <param name="dispRight">出力オプション：シングルチャンネル，16ビット，符号有り整数．入力画像と同じサイズの右視差画像． </param>
/// <param name="state">ステレオマッチング構造体．</param>
#else
/// <summary>
/// Computes the disparity map using graph cut-based algorithm
/// </summary>
/// <param name="left">The left single-channel, 8-bit image. </param>
/// <param name="right">The right image of the same size and the same type. </param>
/// <param name="dispLeft">The optional output single-channel 16-bit signed left disparity map of the same size as input images. </param>
/// <param name="dispRight">The optional output single-channel 16-bit signed right disparity map of the same size as input images. </param>
/// <param name="state">Stereo correspondence structure. </param>
#endif
public static void FindStereoCorrespondenceGC(CvArr left, CvArr right, CvArr dispLeft, CvArr dispRight, CvStereoGCState state)
{
FindStereoCorrespondenceGC(left, right, dispLeft, dispRight, state, false);
}