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