eval_msd_linear_warp

 ==============================================================
 EVAL_MSD_CPS_WARP: get similarity score between CPS warped image and
                    reference. (Evaluare the clamped-plate spline warp using
                    mean-squared-difference)

 Code written by Katherine Smith, 2003

    GENERAL

      score = eval_msd_cps_warp(params, start_points_vec, ref_image_vec)

    INPUT/S

      -params:
           The paramters of the warps.

           params(1): warp centre
           params(2): r
           params(3): d

      -start_points_vector:
           Points to be warped?

      -ref_image_vec:
           The reference image vector.
           (Reference image vector to be compared to warped image).
           
    OUTPUT/S

      -score:
           The similarity score w.r.t. the reference image. 
           (Mean-squared difference score)

    PENDING WORK

      -

    KNOWN BUG/S

      -None.

    COMMENT/S

      -

    RELATED FUNCTION/S

      LINEAR_WARP, POOR_LINEAR_WARP, CPS_WARP_1D, MSD, EVAL_MSD, 
      EVAL_MODEL_MULTI_WARP

    ABOUT

      -Created:     November 23rd, 2003
      -Last update: Novermber 27th, 2003
      -Revision:    0.0.4
      -Author:      R. S. Schestowitz, University of Manchester
 ==============================================================

0001 function score = eval_msd_cps_warp(params, start_points_vec, ref_image_vec)
0002 % ==============================================================
0003 % EVAL_MSD_CPS_WARP: get similarity score between CPS warped image and
0004 %                    reference. (Evaluare the clamped-plate spline warp using
0005 %                    mean-squared-difference)
0006 %
0007 % Code written by Katherine Smith, 2003
0008 %
0009 %    GENERAL
0010 %
0011 %      score = eval_msd_cps_warp(params, start_points_vec, ref_image_vec)
0012 %
0013 %    INPUT/S
0014 %
0015 %      -params:
0016 %           The paramters of the warps.
0017 %
0018 %           params(1): warp centre
0019 %           params(2): r
0020 %           params(3): d
0021 %
0022 %      -start_points_vector:
0023 %           Points to be warped?
0024 %
0025 %      -ref_image_vec:
0026 %           The reference image vector.
0027 %           (Reference image vector to be compared to warped image).
0028 %
0029 %    OUTPUT/S
0030 %
0031 %      -score:
0032 %           The similarity score w.r.t. the reference image.
0033 %           (Mean-squared difference score)
0034 %
0035 %    PENDING WORK
0036 %
0037 %      -
0038 %
0039 %    KNOWN BUG/S
0040 %
0041 %      -None.
0042 %
0043 %    COMMENT/S
0044 %
0045 %      -
0046 %
0047 %    RELATED FUNCTION/S
0048 %
0049 %      LINEAR_WARP, POOR_LINEAR_WARP, CPS_WARP_1D, MSD, EVAL_MSD,
0050 %      EVAL_MODEL_MULTI_WARP
0051 %
0052 %    ABOUT
0053 %
0054 %      -Created:     November 23rd, 2003
0055 %      -Last update: Novermber 27th, 2003
0056 %      -Revision:    0.0.4
0057 %      -Author:      R. S. Schestowitz, University of Manchester
0058 % ==============================================================
0059 
0060 warped_points = cps_warp_1d(start_points_vec,params(1),params(2),params(3));
0061     % warp the points
0062 warped_image = interp1(start_points_vec,ref_image_vec,warped_points); 
0063     % interploate image to apply warp
0064 % warp image (rather use the warped points to interpolate the image)
0065 score = msd(ref_image_vec, warped_image); 
0066     % evaluate mean squared difference between reference and warped image