c - 在 C 中优化双线性调整大小算法

Question

任何人都可以在下一个双线性调整算法中发现任何提高速度的方法吗？ 我需要提高速度，因为这是保持良好图像质量的关键。预计用于具有低速 CPU 的移动设备。 该算法主要用于放大调整大小。任何其他更快的双线性算法也将不胜感激。谢谢

void resize(int* input, int* output, int sourceWidth, int sourceHeight, int targetWidth, int targetHeight) 
{    
    int a, b, c, d, x, y, index;
    float x_ratio = ((float)(sourceWidth - 1)) / targetWidth;
    float y_ratio = ((float)(sourceHeight - 1)) / targetHeight;
    float x_diff, y_diff, blue, red, green ;
    int offset = 0 ;

    for (int i = 0; i < targetHeight; i++) 
    {
        for (int j = 0; j < targetWidth; j++) 
        {
            x = (int)(x_ratio * j) ;
            y = (int)(y_ratio * i) ;
            x_diff = (x_ratio * j) - x ;
            y_diff = (y_ratio * i) - y ;
            index = (y * sourceWidth + x) ;                
            a = input[index] ;
            b = input[index + 1] ;
            c = input[index + sourceWidth] ;
            d = input[index + sourceWidth + 1] ;

            // blue element
            blue = (a&0xff)*(1-x_diff)*(1-y_diff) + (b&0xff)*(x_diff)*(1-y_diff) +
                   (c&0xff)*(y_diff)*(1-x_diff)   + (d&0xff)*(x_diff*y_diff);

            // green element
            green = ((a>>8)&0xff)*(1-x_diff)*(1-y_diff) + ((b>>8)&0xff)*(x_diff)*(1-y_diff) +
                    ((c>>8)&0xff)*(y_diff)*(1-x_diff)   + ((d>>8)&0xff)*(x_diff*y_diff);

            // red element
            red = ((a>>16)&0xff)*(1-x_diff)*(1-y_diff) + ((b>>16)&0xff)*(x_diff)*(1-y_diff) +
                  ((c>>16)&0xff)*(y_diff)*(1-x_diff)   + ((d>>16)&0xff)*(x_diff*y_diff);

            output [offset++] = 
                    0x000000ff | // alpha
                    ((((int)red)   << 24)&0xff0000) |
                    ((((int)green) << 16)&0xff00) |
                    ((((int)blue)  << 8)&0xff00);
        }
    }
}

Answer 1

在我的脑海中:

1. 停止使用浮点，除非您确定您的 objective-c PU 在硬件中具有良好的性能。
2. 确保内存访问是缓存优化的，即聚集在一起。
3. 尽可能使用最快的数据类型。有时这意味着最小，有时意味着“最原生，需要最少的开销”。
4. 调查有符号/无符号整数运算是否会在您的平台上产生性能成本。
5. 调查查找表而不是计算是否能为您带来任何好处(但这些可能会破坏缓存，所以要小心)。

当然，还要进行大量分析和测量。