Complexity reduction method for ultrasound imaging enhancement in tetrolet transform domain

Medical ultrasound images are often very obscure due to the capture devices used. As medical ultrasound images can provide information regarding potential pathological changes and abnormalities, images must be preserved and enhanced to help doctors to monitor the course of diseases. This work proposes using the energy concentration characteristics of tetrolet transform (TT) to preserve texture information and integrate the technique of adaptive histogram equalization (AHE) in order to automatically adjust the ultrasound image contrast, thereby resolving the aforementioned problems. However, the implementation of the TT in software structure brings issues such as computational complexity and large frame buffer use. In view of these problems, this work proposes a low-complexity matching pattern (LMP) method to reduce the space complexity. The LMP is combined with a look-up table approach that solves the issue of the excessive calculations generated in AHE during linear interpolation. The experimental results indicate that the modified algorithm is applicable in ultrasound imaging systems as it is able to improve calculation times.