Question

我有两个像素流，基本上需要对它们进行自定义xor以获得最终结果。它工作得很好 - 唯一的问题是，它需要模拟器大约4秒来解析代码。我知道必须有一种方法来优化这个例程 - 但经过几天测试我的想法（无济于事）后，我正在寻求帮助！

这是我的代码 - 提前感谢任何建议！

             //rawPic1Data and rawPic2Data is a stream of unsigned chars that ultimately came from a UIImage

                for (int i = 0 ; i < (bufferLength); i=i+4)
                {

                    sred = (int)(rawPic1Data[i + 0]);
                    sgreen = (int)(rawPic1Data[i + 1]);
                    sblue = (int)(rawPic1Data[i + 2]);

                    rred = (int)(rawPic2Data[i + 0]);
                    rgreen = (int)(rawPic2Data[i + 1]);
                    rblue = (int)(rawPic2Data[i + 2]);

                    fred = 0;
                    fgreen = 0;
                    fblue = 0;
                    falpha = 0;

                    if (((sred == 102) && (sgreen == 0) && (sblue == 153)) || ((rred == 102) && (rgreen == 0) && (rblue == 153)))
                    {
                        fred = 102; fgreen = 0; fblue = 153; falpha = 255;
                    }
                    else if (((sred == 153) && (sgreen == 51) && (sblue == 204)) || ((rred == 153) && (rgreen == 51) && (rblue == 204)))
                    {
                        fred = 153; fgreen = 51; fblue = 204; falpha = 255;
                    }

                     //...repeat the elseifs for another 12 colors.  (14 total)
                }

            //Use the f values for my final output...

Answer 1

不要自己走像素缓冲区，这将非常缓慢。在CoreImage中使用自定义过滤器执行此类操作。

Answer 2

您可以做的一件事是将每个流中的三个值组合成一个更大的变量。这将允许您同时对所有三个进行比较，因此您的代码中将有三分之一的比较。

sred = (int)(rawPic1Data[i + 0]);
sgreen = (int)(rawPic1Data[i + 1]);
sblue = (int)(rawPic1Data[i + 2]);
register unsigned sval = (sred << 16) | (sgreen << 8) | (sblue);

rred = (int)(rawPic2Data[i + 0]);
rgreen = (int)(rawPic2Data[i + 1]);
rblue = (int)(rawPic2Data[i + 2]);
register unsigned rval = (rred << 16) | (rgreen << 8) | (rblue);

fred = 0;
fgreen = 0;
fblue = 0;
falpha = 0;

if(sval == ((102<<16)|(153) || rval == ((102<<16)|(153)) {
    fred = 102; fgreen = 0; fblue = 153; falpha = 255;
} else if(sval == ((153<<16)|(51<<8)|(204))) || rval = ((153<<16)|(51<<8)|(204)))) {
    fred = 153; fgreen = 51; fblue = 204; falpha = 255;
} ...

像这样的优化加速了我的测试程序36.5％，只有5个测试用例。

更快的像素枚举

2 个答案: