双三次插值算法的图像缩放 [英] Bi-Cubic Interpolation Algorithm for Image Scaling

问题描述

我想写一个基本的双三次调整算法来调整的24位RGB位图。我有 算算一个大致的了解 参与进来，和我使用的<一个href="http://$c$c.google.com/a/eclipselabs.org/p/bicubic-interpolation-image-processing/source/browse/trunk/libimage.c">this实施从谷歌code作为指南。我没有使用任何外部库在这里 - 我只是与算法本身的实验。位图是psented作为一个普通的的std ::矢量＆lt重新$ P $; unsigned char型＆GT; ：

I'm trying to write a basic bicubic resize algorithm to resize a 24-bit RGB bitmap. I have a general understanding of the math involved, and I'm using this implementation from Google Code as a guide. I'm not using any external libraries here - I'm just experimenting with the algorithm itself. The bitmap is represented as a plain std::vector<unsigned char>:

inline unsigned char getpixel(const std::vector<unsigned char>& in, 
    std::size_t src_width, std::size_t src_height, unsigned x, unsigned y, int channel)
{
    if (x < src_width && y < src_height)
        return in[(x * 3 * src_width) + (3 * y) + channel];

    return 0;
}

std::vector<unsigned char> bicubicresize(const std::vector<unsigned char>& in, 
    std::size_t src_width, std::size_t src_height, std::size_t dest_width, std::size_t dest_height)
{
    std::vector<unsigned char> out(dest_width * dest_height * 3);

    const float tx = float(src_width) / dest_width;
    const float ty = float(src_height) / dest_height;
    const int channels = 3;
    const std::size_t row_stride = dest_width * channels;

    unsigned char C[5] = { 0 };

    for (int i = 0; i < dest_height; ++i)
    {
        for (int j = 0; j < dest_width; ++j)
        {
            const int x = int(tx * j);
            const int y = int(ty * i);
            const float dx = tx * j - x;
            const float dy = ty * i - y;

            for (int k = 0; k < 3; ++k)
            {
                for (int jj = 0; jj < 4; ++jj)
                {
                    const int z = y - 1 + jj;
                    unsigned char a0 = getpixel(in, src_width, src_height, z, x, k);
                    unsigned char d0 = getpixel(in, src_width, src_height, z, x - 1, k) - a0;
                    unsigned char d2 = getpixel(in, src_width, src_height, z, x + 1, k) - a0;
                    unsigned char d3 = getpixel(in, src_width, src_height, z, x + 2, k) - a0;
                    unsigned char a1 = -1.0 / 3 * d0 + d2 - 1.0 / 6 * d3;
                    unsigned char a2 = 1.0 / 2 * d0 + 1.0 / 2 * d2;
                    unsigned char a3 = -1.0 / 6 * d0 - 1.0 / 2 * d2 + 1.0 / 6 * d3;
                    C[jj] = a0 + a1 * dx + a2 * dx * dx + a3 * dx * dx * dx;

                    d0 = C[0] - C[1];
                    d2 = C[2] - C[1];
                    d3 = C[3] - C[1];
                    a0 = C[1];
                    a1 = -1.0 / 3 * d0 + d2 -1.0 / 6 * d3;
                    a2 = 1.0 / 2 * d0 + 1.0 / 2 * d2;
                    a3 = -1.0 / 6 * d0 - 1.0 / 2 * d2 + 1.0 / 6 * d3;
                    out[i * row_stride + j * channels + k] = a0 + a1 * dy + a2 * dy * dy + a3 * dy * dy * dy;
                }
            }
        }
    }

    return out;
}

问题：当我使用这种算法为下限值的图像，它的工作原理只是输出图像包含了所有黑色像素右侧出于某种原因，表面上看起来是它被裁剪。

Problem: When I use this algorithm to downscale an image, it works except the output image contains all black pixels on the right side for some reason, giving the appearance that it's been "cropped".

示例：

输入图像：

输出图像：

的问题的：回顾算法，我不明白为什么会发生这种事。有谁看到了破绽吗？

Question: Reviewing the algorithm, I can't see why this would happen. Does anyone see the flaw here?

推荐答案

尽量不要交换的宽度和高度。

try not exchanging width and height.

   for (int i = 0; i < dest_width; ++i)
    {
        for (int j = 0; j < dest_height; ++j)

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