Image registration is a basic problem during image analysis and image processing. Image registration has been widely applied in the fields of medical image

remote sensing and computer vision. This paper investigates two registration methods for ultrasound image relying on the intensity-based similarity measure. In tiw first method intensity information is provided by feature points which have been extracted using Harris corner detector. The registration similarity measure is then defined as a cost-function-error cost function. In the latter method the same cost-function is employed

but uniqueness control and region correspondence are different from the first method. Given this similarity measure

parametric ultrasound image registration is stated as a minimization issue. The experiment even exploits polynomial technique to transform the whole image dataset and estimates the sum of square error in the first method. Image quality is one of the most important issues in ultrasound imaging. Ultrasound images tend to be noisy due to the presence of speckle. Speckle originates from the constructive-destructive interference of the ultrasound pulses

and is produced to some extent by all ultrasound machines. This paper shows that it is possible to perform accurate registration on data from in-vivo examinations. The result indicates that the two methods are robust and meet our requirements

but the latter outperforms the first one. It can match B-scans and areas with certain angel

severe deformation and even with plus noise.