eval_wavelet_single_point

 OPTIMISE_GROUPWISE: Uses PDF's to minimise group-wise complexity

    GENERAL

      function [score, warped_points] = 
       eval_groupwise_single_point(params, warp_centre, r, unwarped_image_vec,
       unwarped_points_vec, image_set, points_set, n_modes, start_points_vec,
       model_evaluation_method, weighting_normalisation_method, shape_weight,
       variation_kept)

 
    INPUT/S

      -X:
          X
           
    OUTPUT/S

      -X:
           X

    PENDING WORK
      
      

    KNOWN BUG/S

      

    COMMENT/S

      

    RELATED FUNCTION/S

      

    ABOUT
      -Created:     February 9th, 2004
      -Last update: February 2004
      -Revision:    0.1.0
      -Author:      R. S. Schestowitz, University of Manchester
 ==============================================================

0001 function [score, warped_points] = eval_waveletsingle_point (params, warp_centre, r, unwarped_image_vec, unwarped_points_vec, image_set, points_set, n_modes, start_points_vec, model_evaluation_method, weighting_normalisation_method, shape_weight, variation_kept, wavelet_evaluation_method, filter, filter_level)
0002 % OPTIMISE_GROUPWISE: Uses PDF's to minimise group-wise complexity
0003 %
0004 %    GENERAL
0005 %
0006 %      function [score, warped_points] =
0007 %       eval_groupwise_single_point(params, warp_centre, r, unwarped_image_vec,
0008 %       unwarped_points_vec, image_set, points_set, n_modes, start_points_vec,
0009 %       model_evaluation_method, weighting_normalisation_method, shape_weight,
0010 %       variation_kept)
0011 %
0012 %
0013 %    INPUT/S
0014 %
0015 %      -X:
0016 %          X
0017 %
0018 %    OUTPUT/S
0019 %
0020 %      -X:
0021 %           X
0022 %
0023 %    PENDING WORK
0024 %
0025 %
0026 %
0027 %    KNOWN BUG/S
0028 %
0029 %
0030 %
0031 %    COMMENT/S
0032 %
0033 %
0034 %
0035 %    RELATED FUNCTION/S
0036 %
0037 %
0038 %
0039 %    ABOUT
0040 %      -Created:     February 9th, 2004
0041 %      -Last update: February 2004
0042 %      -Revision:    0.1.0
0043 %      -Author:      R. S. Schestowitz, University of Manchester
0044 % ==============================================================
0045 
0046 %d = params(1);
0047 start_points = unwarped_points_vec;
0048 max_d = 0.67;
0049 
0050 if (any((abs(params) > max_d)) | any(warp_centre-r <-1) | any(warp_centre+r > 1))
0051   score = realmax;
0052   warped_points = unwarped_points_vec;
0053 else
0054   for i=1:size(params,2)
0055     warped_points = cps_warp_1d(start_points_vec,warp_centre(i),r(i),params(i));
0056     start_points = warped_points;
0057   end
0058   warped_image = interp1(unwarped_points_vec,unwarped_image_vec,warped_points, 'linear',0);
0059   image_set(:,size(image_set,2)+1) = warped_image;
0060   points_set(:,size(points_set,2)+1) = warped_points;
0061 
0062   
0063   % Note RSS: compute pdf of the intensities
0064   % evaluate using log(pdf) to return a score
0065   
0066   compressed_data = compute_wavelet(image_set, points_set, filter, filter_level);
0067   score = measure_wavelet(compressed_data, wavelet_evaluation_method, warped_image);
0068   
0069   % Change above: addition of warped_points -- needs to be added to
0070   % multi_point too
0071 end