改进量子粒子群优化算法在图像增强中的研究磁

摘要

An image enhancement method with optimization problem is proposed as the lack of adaptability of traditional methods .Firstly a QPSO-tp(time varying parameters Quantum-behaved Particle Swarm Optimization ) algorithm is presen-ted ,and standard test function experimental results show that the improved algorithm is superior to original QPSO (Quan-tum-behaved Particle Swarm Optimization ) algorithm on global search ability and convergence accuracy ,and it has few ad-justable parameters and stronger randomness .Secondly the nonlinear-transform enhancement of remote sensing gray-scale image is processed with the QPSO-tp algorithm for optimization parameters .The experimental results show that the image enhancement effect is improved significantly .%由于传统的图像增强方法在适应性方面存在不足，论文提出一种改进的图像增强方法。这种改进的算法是实变参数量子粒子群优化 QPSO-tp 算法。实验结果表明，改进后的算法在全局搜索能力和收敛精度上要优于原 QPSO 算法，具有调节参数少、随机性更强等优点。接着将遥感灰度图像的非线性变换增强过程用最优化问题进行处理，用 QPSO-tp 算法进行参数寻优，能够极大的提高图像的增强效果。