Doc: Lossless JPEG clarifications

- Clarify that lossless JPEG is slower than and doesn't compress as well
  as lossy JPEG.  (That should be obvious, because "lossy" literally
  means that data is thrown away.)
- Re-generate TurboJPEG C API documentation using Doxygen 1.9.8.
- Clarify that setting the data_precision field in jpeg_compress_struct
  to 16 requires lossless mode.
- Explain what the predictor selection value actually does.  (Refer to
  Recommendation ITU-T T.81 (1992) | ISO/IEC 10918-1:1994, Section
  H.1.2.1.)

turbojpeg.h

@@ -621,9 +621,11 @@ enum TJPARAM {
    * lossless/predictive.
    *
    * In most cases, compressing and decompressing lossless JPEG images is
-   * considerably slower than compressing and decompressing lossy JPEG images.
-   * Also note that the following features are not available with lossless JPEG
-   * images:
+   * considerably slower than compressing and decompressing lossy JPEG images,
+   * and lossless JPEG images are much larger than lossy JPEG images.  Thus,
+   * lossless JPEG images are typically used only for applications that require
+   * mathematically lossless compression.  Also note that the following
+   * features are not available with lossless JPEG images:
    * - Colorspace conversion (lossless JPEG images always use #TJCS_RGB,
    * #TJCS_GRAY, or #TJCS_CMYK, depending on the pixel format of the source
    * image)
@@ -645,6 +647,30 @@ enum TJPARAM {
    * **Value**
    * - `1`-`7` *[default for compression: `1`]*
    *
+   * Lossless JPEG compression shares no algorithms with lossy JPEG
+   * compression.  Instead, it uses differential pulse-code modulation (DPCM),
+   * an algorithm whereby each sample is encoded as the difference between the
+   * sample's value and a "predictor", which is based on the values of
+   * neighboring samples.  If Ra is the sample immediately to the left of the
+   * current sample, Rb is the sample immediately above the current sample, and
+   * Rc is the sample diagonally to the left and above the current sample, then
+   * the relationship between the predictor selection value and the predictor
+   * is as follows:
+   *
+   * PSV | Predictor
+   * ----|----------
+   * 1   | Ra
+   * 2   | Rb
+   * 3   | Rc
+   * 4   | Ra + Rb – Rc
+   * 5   | Ra + (Rb – Rc) / 2
+   * 6   | Rb + (Ra – Rc) / 2
+   * 7   | (Ra + Rb) / 2
+   *
+   * Predictors 1-3 are 1-dimensional predictors, whereas Predictors 4-7 are
+   * 2-dimensional predictors.  The best predictor for a particular image
+   * depends on the image.
+   *
    * @see #TJPARAM_LOSSLESS
    */
   TJPARAM_LOSSLESSPSV,