11 UESTC-RSIP
RSTP 12
12 UESTC-RSIP
UE 13
13 UESTC-RSIP
Image Registration Algorithm classification Intensity-based VS feature-based Intensity-based methods compare intensity patterns in images via correlation metrics,while feature-based methods find correspondence between image features such as points,lines,and contours. Generally,sub-images that are extracted from the reference and target images,are used for image similarity comparison.If sub-images are registered, centers of corresponding sub-images are treated as corresponding feature points. 14
Image Registration Algorithm classification Intensity-based VS feature-based Intensity-based methods compare intensity patterns in images via correlation metrics, while feature-based methods find correspondence between image features such as points, lines, and contours. Generally, sub-images that are extracted from the reference and target images, are used for image similarity comparison. If sub-images are registered, centers of corresponding sub-images are treated as corresponding feature points. 14 UESTC-RSIP
Transformation models linear transformations VS 'nonrigid'transformations linear transformations,which include rotation,scaling, translation,and other transforms.Linear transformations are global in nature,thus,they cannot model local geometric differences between images. nonrigid'transformations are capable of locally warping the target image to align with the reference image
Transformation models linear transformations VS 'nonrigid' transformations linear transformations, which include rotation, scaling, translation, and other transforms. Linear transformations are global in nature, thus, they cannot model local geometric differences between images. 'nonrigid' transformations are capable of locally warping the target image to align with the reference image. UESTC-RSIP