measure_model_msd

 ==============================================================
 MEASURE_MODEL_MSD: Measure the reference against a set of images using
                    mean-squared-differences and return mean.

 Code written by Katherine Smith, 2003

    GENERAL

      score = measure_model_msd(warped_images)

    INPUT/S

      -warped_images:
           A set of images (similar to the model).
           
    OUTPUT/S

      -score:
           Mean-squared difference score.

    PENDING WORK

      -

    KNOWN BUG/S

      -None.

    COMMENT/S

      -The name is misleading because models are not involved. Consider
      renaming.

    RELATED FUNCTION/S

      MSD, EVAL_MSD

    ABOUT

      -Created:     November 23rd, 2003
      -Last update: February 18th, 2004
      -Revision:    0.0.9
      -Author:      R. S. Schestowitz, University of Manchester
 ==============================================================

0001 function score = measure_model_msd(warped_images)
0002 % ==============================================================
0003 % MEASURE_MODEL_MSD: Measure the reference against a set of images using
0004 %                    mean-squared-differences and return mean.
0005 %
0006 % Code written by Katherine Smith, 2003
0007 %
0008 %    GENERAL
0009 %
0010 %      score = measure_model_msd(warped_images)
0011 %
0012 %    INPUT/S
0013 %
0014 %      -warped_images:
0015 %           A set of images (similar to the model).
0016 %
0017 %    OUTPUT/S
0018 %
0019 %      -score:
0020 %           Mean-squared difference score.
0021 %
0022 %    PENDING WORK
0023 %
0024 %      -
0025 %
0026 %    KNOWN BUG/S
0027 %
0028 %      -None.
0029 %
0030 %    COMMENT/S
0031 %
0032 %      -The name is misleading because models are not involved. Consider
0033 %      renaming.
0034 %
0035 %    RELATED FUNCTION/S
0036 %
0037 %      MSD, EVAL_MSD
0038 %
0039 %    ABOUT
0040 %
0041 %      -Created:     November 23rd, 2003
0042 %      -Last update: February 18th, 2004
0043 %      -Revision:    0.0.9
0044 %      -Author:      R. S. Schestowitz, University of Manchester
0045 % ==============================================================
0046 
0047 n_images = size(warped_images,2); 
0048           % get number of images
0049 ref_image = warped_images(:,1);
0050           % set reference image
0051 for i=1:n_images
0052   score(i) = msd(ref_image, warped_images(:,i)); 
0053           % record the squared mean difference of all images against the reference
0054 end
0055 score = mean(score); 
0056           % get the mean score