| Summary: | 碩士 === 國立臺灣科技大學 === 電機工程系 === 96 === Ultrasound imaging has become widely utilized for clinical diagnoses. Nevertheless, detection of low-contrast object in ultrasound images is significantly limited by inherent speckle artifacts. For speckle suppression using post-processing filtering, in this paper, we proposed two novel adaptive filters based on directional brightness differences (BD). The adaptive weighted median filter (AWMF) relies on statistic features of local image brightness. Though the spatial characteristics may significantly differ, a resolvable object could be erroneously blurred when it is statistically similar to speckle. The method 1 for median weighting is proposed to better separate resolvable objects from speckle background by the maximal brightness difference (MBD) of directional kernels. Since resolvable objects usually have distinct spatial orientation, a large brightness difference is expected among directional kernels with the same orientation. For speckles, the random fluctuation of brightness would result in low brightness difference for all directions. The method 2 of the median value in each direction is weighted by the BD of that angle. For a homogeneous region, the BD is similar in all directions and the median values are equally weighted for maximal smoothing. On the other hand, a large BD is detected in one specific angle when the mask covers a resolvable contour. The filter preserves the contour by giving the median value along that direction a larger weighting. The novel filters were examined using simulated and in-vivo ultrasound images. Results show that they are superior to the AWMF filter in computational efficiency and detail preserving with similar speckle suppression.
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