image_pipeline-1.1.0 has been released into latest. This is a development
release; it is recommended for users to keep using the 1.0 branch in
boxturtle. For more information see
http://www.ros.org/wiki/StackVersionPolicy.

The major new features are in stereo_image_proc. It takes advantage of
improvements to the OpenCV stereo block matcher, particularly to reduce
fringe artifacts at edges. For comparison, the reference implementation of
stereo block matching (on which OpenCV's was based) can be used instead, but
they should now give roughly the same results. stereo_image_proc now
advertises a separate point cloud topic using the new and improved
PointCloud2<http://www.ros.org/doc/api/sensor_msgs/html/msg/PointCloud2.html>message
type.

Cheers,
Patrick

For the full changelist see
http://www.ros.org/wiki/image_pipeline/ChangeList

camera_calibration:

   - calibration no longer makes buggy assumptions about corner spacing
   always being .108m
   - Added a simple calibration script (camera_calibrate_from_disk.py) that
   loads a set of images from disk and performs monocular calibration returning
   the camera intrinsics.
   - Set projection matrix P correctly in monocular calibration.

image_proc:

   - Warn if color topic requested but raw image data is grayscale.

stereo_image_proc:

   - Allow using either the OpenCV block matcher or the Willow Garage
   reference implementation. Should give roughly the same results with
   vision_opencv 1.1 or greater.
   -

   Added points2 topic with the new
sensor_msgs/PointCloud2<http://ros.org/doc/api/sensor_msgs/html/msg/PointCloud2.html>format.
   - Upped texture_threshold maximum to 10000; high values needed for
   simulated stereo images.