【快速阅读三】使用泊松融合实现单幅图的无缝拼贴及消除两幅图片直接的拼接缝隙。

void IM_SeamlessTiling(unsigned char* Src, unsigned char* Dest, int Width, int Height, int Stride)
{
    int Channel = Stride / Width;
    unsigned char* Fore = (unsigned char*)malloc(Height * Stride * sizeof(unsigned char));
    unsigned char* Mask = (unsigned char*)calloc(Height * Width, sizeof(unsigned char));
    memcpy(Fore, Src, Height * Stride);
    //    上下边界和左右边界设为原图像的边界和的一半。
    for (int X = 0; X < Width * Channel; X++)
    {
        Fore[X] = (Src[X] + Src[(Height - 1) * Stride + X]) / 2;
        Fore[(Height - 1) * Stride + X] = Fore[X];
    }
    for (int Y = 1; Y < Height - 1; Y++)
    {
        for (int C = 0; C < Channel; C++)
        {
            Fore[Y * Stride + C] = (Src[Y * Stride + C] + Src[Y * Stride + (Width - 1) * Channel + C]) / 2;
            Fore[Y * Stride + (Width - 1) * Channel + C] = Fore[Y * Stride + C];
        }
    }
    memset(Mask , 255, Width * Height);
    //    然后引导向量场仍然使用原图像的梯度场。这样得到的结果就可以用来无缝拼接
    //    最后一个参数为0，倒数第二个参数也为，Mask设置为全255，则就是直接使用Src的梯度场了
    IM_NormalClone(Fore, Src, Mask, Dest, Width, Height, Stride, 0, 0);
    free(Fore);
    free(Mask);
}

    Mat Kernel(Size(3, 3), CV_8UC1);
    Kernel.setTo(Scalar(1));
    erode(binaryMask, binaryMask, Kernel, Point(-1,-1), 3);

void IM_InnerSeamlessStitching(HBitmap Src1, HBitmap Src2, HBitmap Dest1, HBitmap Dest2, int Direction)
{
    int Channel = Src1.Stride / Src1.Width;
    if (Src1.PixelFormat != Src1.PixelFormat)                return;
    if ((Direction == 0) && (Src1.Height != Src2.Height))    return;
    if ((Direction == 1) && (Src1.Width != Src2.Width))        return;

    unsigned char* Fore1 = (unsigned char*)malloc(Src1.Height * Src1.Stride * sizeof(unsigned char));
    unsigned char* Fore2 = (unsigned char*)malloc(Src2.Height * Src2.Stride * sizeof(unsigned char));
    unsigned char* Mask1 = (unsigned char*)calloc(Src1.Height * Src1.Width, sizeof(unsigned char));
    unsigned char* Mask2 = (unsigned char*)calloc(Src2.Height * Src2.Width, sizeof(unsigned char));

    memcpy(Fore1, Src1.Scan0, Src1.Height * Src1.Stride);
    memcpy(Fore2, Src2.Scan0, Src2.Height * Src2.Stride);

    //    水平方向融合
    if (Direction == 0)
    {
        for (int Y = 0; Y < Src1.Height; Y++)
        {
            if (Channel == 1)
            {
                int Avg = (Src1.Scan0[Y * Src1.Stride + Src1.Width - 1] + Src2.Scan0[Y * Src2.Stride]) / 2;
                Fore1[Y * Src1.Stride + Src1.Width - 1] = Avg;
                Fore2[Y * Src2.Stride] = Avg;
            }
            else
            {
                int AvgB = (Src1.Scan0[Y * Src1.Stride + (Src1.Width - 1) * 3 + 0] + Src2.Scan0[Y * Src2.Stride + 0]) / 2;
                int AvgG = (Src1.Scan0[Y * Src1.Stride + (Src1.Width - 1) * 3 + 1] + Src2.Scan0[Y * Src2.Stride + 1]) / 2;
                int AvgR = (Src1.Scan0[Y * Src1.Stride + (Src1.Width - 1) * 3 + 2] + Src2.Scan0[Y * Src2.Stride + 2]) / 2;
                Fore1[Y * Src1.Stride + (Src1.Width - 1) * 3 + 0] = AvgB;
                Fore1[Y * Src1.Stride + (Src1.Width - 1) * 3 + 1] = AvgG;
                Fore1[Y * Src1.Stride + (Src1.Width - 1) * 3 + 2] = AvgR;
                Fore2[Y * Src2.Stride + 0] = AvgB;
                Fore2[Y * Src2.Stride + 1] = AvgG;
                Fore2[Y * Src2.Stride + 2] = AvgR;
            }
        }
    }
    else if (Direction == 1)
    {
        for (int X = 0; X < Src1.Width * Channel; X++)
        {
            //    上下两个可以采用不一样的值，但是做点融合也是不错的,实测还是有点小问题
            //    Fore1[(Src1.Height - 1) * Src1.Stride + X] = (Src1.Scan0[(Src1.Height - 1) * Src1.Stride + X] * 77 + Src2.Scan0[X] * 51) / 128;
            //    Fore2[X] = (Src1.Scan0[(Src1.Height - 1) * Src1.Stride + X] * 51 + Src2.Scan0[X] * 77) / 128;*/
            
            int Avg = (Src1.Scan0[(Src1.Height - 1) * Src1.Stride + X] + Src2.Scan0[X]) / 2;
            Fore1[(Src1.Height - 1) * Src1.Stride + X] = Avg;
            Fore2[X] = Avg;
        }
    }
    memset(Mask1, 255, Src1.Width * Src1.Height);
    memset(Mask2, 255, Src2.Width * Src2.Height);
    //    然后引导向量场仍然使用原图像的梯度场。这样得到的结果就可以用来无缝拼接
    //    最后一个参数为0，倒数第二个参数也为，Mask设置为全255，则就是直接使用Src的梯度场了
    IM_NormalClone(Fore1, Src1.Scan0, Mask1, Dest1.Scan0, Src1.Width, Src1.Height, Src1.Stride, 0, 0);
    IM_NormalClone(Fore2, Src2.Scan0, Mask2, Dest2.Scan0, Src2.Width, Src2.Height, Src2.Stride, 0, 0);

    free(Fore1);
    free(Fore2);
    free(Mask1);
    free(Mask2);
}