An ultrasound image plays the role of eyes in medical imaging tools, and it can help us to observe the physical lesions. The ultrasound image system captures the image more easily than other medical system, and non-invasive detection can reduce the diagnostic time. It is widely used in a variety of medical treatments and medical testing currently. On the other hand, medical ultrasound images are often unclear due to the capturing devices used. As the medical ultrasound images can provide information regarding potential pathological changes and abnormalities, the images must be preserved and enhanced to help doctors to monitor the course of a disease. This research work proposes to use the energy concentration characteristics of Tetrolet transform to preserve the texture information and integrate the technique of adaptive histogram equalization (AHE) to automatically adjust the contrast of an ultrasound image, thereby to resolve the aforementioned function. However, the implementation of the Tetrolet transform in very large scale integration (VLSI) architecture brings issues such as computational complexity and large memory use. In view of these problems, this research work proposes a low-complexity matching pattern (LMP) to reduce the amount of memory used. The LMP is combined with a look-up table approach to solve the issues of the excessive calculations generated in AHE during linear interpolation. The experimental results indicate that the modified algorithm is applicable in hand-held ultrasound imaging systems as it is able to improve calculation times and hardware. Finally, It was implemented in an Xilinx 7 series ZedBoard Zynq-7000 ARM / FPGA SoC Development Board.