Abstract: Aiming at grayscale image enhancement features, the quantum properties of
chaotic particle swarm optimization studies are used. First, the global optimal solution particles
update their velocity and position; then the probability density function of quantum effects makes
the particle in bound state to appear, with a certain probability, anywhere in the entire feasible
search space ; the chaotic state makes the particles change from disorder to order , with the related
factors avoiding searching blindness; final grayscale image uses nonlinear mapping curve
transformation, and its function is translated into parameters of improved PSO algorithm. The
simulation shows the algorithm excellent for image grayscale enhancement better in quantitative
evaluation and good in time efficiency.

Key words: chaos, quantum, gray enhancement