Based on the traditional particle swarm search algorithm, a new search algorithm is proposed, which is called Adaptive Decision Inertia weight Particle Swarm Optimization (ADI-PSO) correlation searching algorithm. ADI-PSO combines adaptive inertia factor and policy termination, which can continually update inertia factor to accelerate the convergence speed during the iterations. The algorithm can intelligently determine whether to end the iteration, so it can get accurate search results more quickly. Two groups of contrast experiments show that the precision of ADI-PSO algorithm and N-R algorithm are much the same, but the search speed of ADI-PSO is more quickly. In the case of rough speckle image, the optimal fitness value is -0.038 6, 0.888 1, 0.917 6 respectively using three different methods. Compared with PSO and LDI-PSO, the convergence speed of ADI-PSO is more quickly, and the stability is better. Besides, ADI-PSO can overcome premature convergence effectively.