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eval_msd_linear_warp

PURPOSE ^

EVAL_MSD_CPS_WARP: get similarity score between CPS warped image and

SYNOPSIS ^

function score = eval_msd_cps_warp(params, start_points_vec, ref_image_vec)

DESCRIPTION ^

 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
 ==============================================================

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

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

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