RGB转YUV

最新推荐文章于 2025-05-24 08:20:27 发布

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#cuda编程 #图像处理

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本文介绍了使用C语言和CUDA实现RGB24图像格式到YUV420（NV12/YV12）格式的转换方法。C语言实现直接在CPU上运行，而CUDA实现则利用GPU加速处理。两种实现都详细展示了像素颜色空间转换的过程。

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C实现：

void rgb24_to_nv12(uint8_t* data, int w, int h, uint8_t* yuv)
{
    uint32_t row_bytes;
    uint8_t* uv;
    uint8_t* y;
    uint8_t r, g, b;
    uint8_t y_val, u_val, v_val;
    uint32_t off;
    uint32_t off_uv;
    uint8_t* img;
    int i, j;
    y = yuv;
    uv = yuv + w * h;
    off = 0;
    row_bytes = (w * 3 + 3) & ~3;
    h = h & ~1;
    //先转换Y
    for (i = 0; i < h; i++)
    {   
        img = data + off;
        for (j = 0; j < w; j++)
        {
            b = *img++;
            g = *img++;
            r = *img++;
            y_val = (uint8_t)(((int)(30 * r) + (int)(59 * g) + (int)(11 * b)) / 100);
            *y++ = y_val;
        }
        off += row_bytes;
    }
    //转换uv
    off = 0;
    for (i = 0; i < h; i += 2)
    {
        img = data + off;
        for (j = 0; j < w; j+=2)
        {
            b = *img++;
            g = *img++;
            r = *img++;
            img += 3;
            u_val = (uint8_t)(((int)(-17 * r) - (int)(33 * g) + (int)(50 * b) + 12800) / 100);
            v_val = (uint8_t)(((int)(50 * r) - (int)(42 * g) - (int)(8 * b) + 12800) / 100);
            *uv++ = v_val;
            *uv++ = u_val;
        }
        off += row_bytes;
        off += row_bytes;
    }
}

CUDA实现：

#include "cuda_runtime.h"
#include "device_launch_parameters.h"

#define  MEMORY_ALGN_DEVICE  511

__host__ __device__ __forceinline__ int divUp(int total, int grain)
{
    return (total + grain - 1) / grain;
}

__device__ __forceinline__ void rgb_to_y(const uint8_t b, const uint8_t g, const uint8_t r, uint8_t& y)
{
    y = static_cast<uint8_t>(((int)(30 * r) + (int)(59 * g) + (int)(11 * b)) / 100);
}

__device__ __forceinline__ void rgb_to_yuv(const uint8_t b, const uint8_t g, const uint8_t r, uint8_t& y, uint8_t& u, uint8_t& v)
{
    rgb_to_y(b, g, r, y);
    u = static_cast<uint8_t>(((int)(-17 * r) - (int)(33 * g) + (int)(50 * b) + 12800) / 100);
    v = static_cast<uint8_t>(((int)(50 * r) - (int)(42 * g) - (int)(8 * b) + 12800) / 100);
}

__global__ void RGB24_to_YV12_kernel(uint8_t* data,int w, int h, uint32_t row_bytes, uint8_t* y_data, uint8_t* u_data, uint8_t* v_data, uint32_t y_pitch, uint32_t uv_pitch)
    {
        const int x = (blockIdx.x * blockDim.x + threadIdx.x) * 2;
        const int y = (blockIdx.y * blockDim.y + threadIdx.y) * 2;

        if (x + 1 >= w || y + 1 >= h)
            return;

        uint8_t r, g, b;
        uint8_t y_val, u_val, v_val;
        uint8_t* img;
        //pixel at (x, y)
        img = data + y * row_bytes + x * 3;
        b = *img++;
        g = *img++;
        r = *img++;
        rgb_to_y(b, g, r, y_val);
        *(y_data + y * y_pitch + x) = y_val;

        //pixel at (x+1, y)
        b = *img++;
        g = *img++;
        r = *img++;
        rgb_to_y(b, g, r, y_val);
        *(y_data + y * y_pitch + x + 1) = y_val;

        //pixel at (x, y+1)
        img = data + (y+1) * row_bytes + x * 3;
        b = *img++;
        g = *img++;
        r = *img++;
        rgb_to_y(b, g, r,  y_val);
        *(y_data + (y+1) * y_pitch + x) = y_val;

        //pixel at (x+1, y+1)
        b = *img++;
        g = *img++;
        r = *img++;
        rgb_to_yuv(b,g, r, y_val, u_val, v_val);
        *(y_data + (y + 1) * y_pitch + x + 1) = y_val;
        *(u_data + uv_pitch * y / 2 + x / 2) = u_val;
        *(v_data + uv_pitch * y / 2 + x / 2) = v_val;
    }


void RGB24_to_YV12(uint8_t* data, uint8_t* y, uint8_t* u, uint8_t* v, int w, int h)
{
    uint32_t row_bytes;
    uint32_t y_pitch;
    uint32_t uv_pitch;
    const dim3 block(32, 8);
    const dim3 grid(divUp(w, block.x * 2), divUp(h, block.y * 2));
    row_bytes = (w * 3 + 3) & ~3;
    y_pitch = (w + MEMORY_ALGN_DEVICE) & ~MEMORY_ALGN_DEVICE;
    uv_pitch = (w / 2 + MEMORY_ALGN_DEVICE) & ~MEMORY_ALGN_DEVICE;
    RGB24_to_YV12_kernel << <grid, block >> >(data, w, h, row_bytes, y, u, v, y_pitch, uv_pitch);
    cudaGetLastError();
    cudaDeviceSynchronize();
}