Abstract: The CLEANT algorithm is an advanced acoustic imaging algorithm that employs an advanced time-domain iterative deconvolution approach to solve the problem, offering high-resolution acoustic imaging as one of its key advantages.However, the CLEANT algorithm suffers from long computation times, high memory usage, and low computational efficiency. To address these issues, a comprehensive analysis of the CLEANT algorithm was conducted, followed by optimizations such as the restructuring of local loop constructs and the introduction of parallel loop structures based on the serial version. A parallelized implementation of the CLEANT algorithm was proposed, utilizing the Threading Building Blocks (TBB) framework. The optimization process involved reworking local loops and incorporating parallel loops, building on the serial version. Simulation and experimental results demonstrate that the TBB-based parallel CLEANT algorithm achieves significant acceleration compared to its serial counterpart, substantially reducing both computation time and memory usage, while significantly improving computational efficiency.