PNG specification states that there are five possible filters，可以为图像的每一行分别选择。首先给出一些一般性建议：

• 索引彩色和
• 真彩色和灰度图像：“五个滤镜中的任何一个都可能证明是最有效的”
• 如果您只能对整个图像使用一个滤镜，则Paeth可能是最好的

Then it suggests the following，听起来好像是在PNG的开发初期就写的，而且不是很具体：

  

以下简单的启发式方法在早期测试中表现良好：使用所有五个过滤器计算输出扫描线，并选择给出输出绝对值之和最小的过滤器。 （对于此测试，将输出字节视为带符号的差异。）此方法通常胜过任何单个固定滤波器的选择。但是，随着使用PNG的经验越来越多，很有可能会找到更好的启发式方法。

编码器通常如何挑选使用的滤波器？是上述方法中的典型方法还是现代方法？

编辑：
@ Mark-Setchell指向libpng source code，其中包含从第2416行开始的长注释：

/* The prediction method we use is to find which method provides the
 * smallest value when summing the absolute values of the distances
 * from zero,using anything >= 128 as negative numbers.  This is known
 * as the "minimum sum of absolute differences" heuristic.  Other
 * heuristics are the "weighted minimum sum of absolute differences"
 * (experimental and can in theory improve compression),and the "zlib
 * predictive" method (not implemented yet),which does test compressions
 * of lines using different filter methods,and then chooses the
 * (series of) filter(s) that give minimum compressed data size (VERY
 * computationally expensive).
 *
 * GRR 980525:  consider also
 *
 *   (1) minimum sum of absolute differences from running average (i.e.,*       keep running sum of non-absolute differences & count of bytes)
 *       [track dispersion,too?  restart average if dispersion too large?]
 *
 *  (1b) minimum sum of absolute differences from sliding average,probably
 *       with window size <= deflate window (usually 32K)
 *
 *   (2) minimum sum of squared differences from zero or running average
 *       (i.e.,~ root-mean-square approach)
 */