雙線性插值算法ARM NEON優化

C語言版本雙線性插值算法

inline double bilinear_interp(double x, double y, double v11, double v12,
                              double v21, double v22) {

    return (v11 * (1 - y) + v12 * y) * (1 - x) + (v21 * (1 - y) + v22 * y) * x;
}

使用ARM NOEN優化後的雙線性插值版本

inline uint8x8_t bilinear_interp_NEON(double x, double y, uint8x8_t v11,uint8x8_t v12,
                                      uint8x8_t v21,uint8x8_t v22)
{
    uint16x8_t v11_16 = vmovl_u8(v11);
    uint16x8_t v12_16 = vmovl_u8(v12);
    uint16x8_t v21_16 = vmovl_u8(v21);
    uint16x8_t v22_16 = vmovl_u8(v22);

    ///convert v11 to two float32x4
    uint16x4_t v_16_low = vget_low_u16(v11_16);
    uint16x4_t v_16_high = vget_high_u16(v11_16);
    uint32x4_t v_32_low = vmovl_u16(v_16_low);
    uint32x4_t v_32_high = vmovl_u16(v_16_high);
    float32x4_t v11_32f_low = vcvtq_f32_u32(v_32_low);
    float32x4_t v11_32f_high = vcvtq_f32_u32(v_32_high);

    //v12
    v_16_low = vget_low_u16(v12_16);
    v_16_high = vget_high_u16(v12_16);
    v_32_low = vmovl_u16(v_16_low);
    v_32_high = vmovl_u16(v_16_high);
    float32x4_t v12_32f_low = vcvtq_f32_u32(v_32_low);
    float32x4_t v12_32f_high = vcvtq_f32_u32(v_32_high);

    //v21
    v_16_low = vget_low_u16(v21_16);
    v_16_high = vget_high_u16(v21_16);
    v_32_low = vmovl_u16(v_16_low);
    v_32_high = vmovl_u16(v_16_high);
    float32x4_t v21_32f_low = vcvtq_f32_u32(v_32_low);
    float32x4_t v21_32f_high = vcvtq_f32_u32(v_32_high);

    //v22
    v_16_low = vget_low_u16(v22_16);
    v_16_high = vget_high_u16(v22_16);
    v_32_low = vmovl_u16(v_16_low);
    v_32_high = vmovl_u16(v_16_high);
    float32x4_t v22_32f_low = vcvtq_f32_u32(v_32_low);
    float32x4_t v22_32f_high = vcvtq_f32_u32(v_32_high);

    float32_t fx = (float32_t)x;
    float32_t fy = (float32_t)y;
    float32_t one_fx = 1-fx;
    float32_t one_fy = 1-fy;

    float32x4_t tmp1,tmp2,tmp3,tmp4,tmp5,tmp;
    uint32x4_t result_32_low,result_32_high;
    uint16x4_t result_16_low,result_16_high;
    //for low  32x4
    tmp1 = vmulq_n_f32(v11_32f_low, one_fy);
    tmp2 = vmulq_n_f32(v12_32f_low, fy);
    tmp3 = vaddq_f32(tmp1, tmp2);
    tmp4 = vmulq_n_f32(tmp3, one_fx);

    tmp1 = vmulq_n_f32(v21_32f_low, one_fy);
    tmp2 = vmulq_n_f32(v22_32f_low, fy);
    tmp3 = vaddq_f32(tmp1, tmp2);
    tmp5 = vmulq_n_f32(tmp3, fx);

    tmp = vaddq_f32(tmp4, tmp5);
    result_32_low = vcvtq_u32_f32(tmp);
    result_16_low = vqmovn_u32(result_32_low);

    //for high 32x4
    tmp1 = vmulq_n_f32(v11_32f_high, one_fy);
    tmp2 = vmulq_n_f32(v12_32f_high, fy);
    tmp3 = vaddq_f32(tmp1, tmp2);
    tmp4 = vmulq_n_f32(tmp3, one_fx);

    tmp1 = vmulq_n_f32(v21_32f_high, one_fy);
    tmp2 = vmulq_n_f32(v22_32f_high, fy);
    tmp3 = vaddq_f32(tmp1, tmp2);
    tmp5 = vmulq_n_f32(tmp3, fx);

    tmp = vaddq_f32(tmp4, tmp5);
    result_32_high = vcvtq_u32_f32(tmp);
    result_16_high = vqmovn_u32(result_32_high);


    uint16x8_t result_16 = vcombine_u16(result_16_low,result_16_high);

    uint8x8_t result_8 = vqmovn_u16(result_16);
    return result_8; 
}

使用ARM NEON後，一次可以處理8個像素，成倍提高了運行的速度。實踐中需要特別注意對邊界的處理（行的開始和結尾處）。
到這裏我們還不能滿足。要追求更快！！！
注意上面的代碼中雖然用了ARM NEON，但是在ARM 指令集的操作中用到了浮點操作。所以，還可以繼續使用浮點數定點化的優化方式，優化後的代碼如下：

inline uint8x8_t bilinear_interp_NEON_FixedPoint(double x, double y, uint8x8_t v11,uint8x8_t v12,
                                      uint8x8_t v21,uint8x8_t v22)
{
    uint16x8_t v11_16 = vmovl_u8(v11);
    uint16x8_t v12_16 = vmovl_u8(v12);
    uint16x8_t v21_16 = vmovl_u8(v21);
    uint16x8_t v22_16 = vmovl_u8(v22);


    uint16x4_t v_16_low = vget_low_u16(v11_16);
    uint16x4_t v_16_high = vget_high_u16(v11_16);
    uint32x4_t v11_32_low = vmovl_u16(v_16_low);
    uint32x4_t v11_32_high = vmovl_u16(v_16_high);

    v_16_low = vget_low_u16(v12_16);
    v_16_high = vget_high_u16(v12_16);
    uint32x4_t v12_32_low = vmovl_u16(v_16_low);
    uint32x4_t v12_32_high = vmovl_u16(v_16_high);

    v_16_low = vget_low_u16(v21_16);
    v_16_high = vget_high_u16(v21_16);
    uint32x4_t v21_32_low = vmovl_u16(v_16_low);
    uint32x4_t v21_32_high = vmovl_u16(v_16_high);

    v_16_low = vget_low_u16(v22_16);
    v_16_high = vget_high_u16(v22_16);
    uint32x4_t v22_32_low = vmovl_u16(v_16_low);
    uint32x4_t v22_32_high = vmovl_u16(v_16_high);



    unsigned int intX = x*4096;
    unsigned int intY = y*4096;
    unsigned int one_x = 4096-intX;
    unsigned int one_y = 4096-intY;

    uint32_t intX_32 = (uint32_t) intX;
    uint32_t intY_32 = (uint32_t) intY;
    uint32_t oneX_32 = (uint32_t) one_x;
    uint32_t oneY_32 = (uint32_t) one_y;

    uint32x4_t tmp1,tmp2,tmp3,tmp4,tmp5,tmp;
    uint16x4_t result_16_low, result_16_high;
    //for low 4 numbers
    tmp1 = vmulq_n_u32(v11_32_low,oneY_32);
    tmp2 = vmulq_n_u32(v12_32_low, intY_32);
    tmp3 = vaddq_u32(tmp1, tmp2);
    tmp4 = vmulq_n_u32(tmp3, oneX_32);

    tmp1 = vmulq_n_u32(v21_32_low, oneY_32);
    tmp2 = vmulq_n_u32(v22_32_low, intY_32);
    tmp3 = vaddq_u32(tmp1, tmp2);
    tmp5 = vmulq_n_u32(tmp3, intX_32);

    tmp = vaddq_u32(tmp4, tmp5);
    result_16_low = vshrn_n_u32(tmp,16); //shift right 16 bytes
    result_16_low = vrshr_n_u16(result_16_low,8); //shift right 8 bytes, totally 24 bytes

    //for high 4 numbers
    tmp1 = vmulq_n_u32(v11_32_high,oneY_32);
    tmp2 = vmulq_n_u32(v12_32_high, intY_32);
    tmp3 = vaddq_u32(tmp1, tmp2);
    tmp4 = vmulq_n_u32(tmp3, oneX_32);

    tmp1 = vmulq_n_u32(v21_32_high, oneY_32);
    tmp2 = vmulq_n_u32(v22_32_high, intY_32);
    tmp3 = vaddq_u32(tmp1, tmp2);
    tmp5 = vmulq_n_u32(tmp3, intX_32);

    tmp = vaddq_u32(tmp4, tmp5);
    result_16_high = vshrn_n_u32(tmp,16);  //shift right 16 bytes
    result_16_high = vrshr_n_u16(result_16_high,8);  //shift right 8 bytes, totally 24 bytes

    uint16x8_t result_16 = vcombine_u16(result_16_low,result_16_high);

    uint8x8_t result_8 = vqmovn_u16(result_16);
    return result_8;

}

加入浮點定點化之後的優化，時間能進一步提升一倍左右。