基于改进量子遗传算法的图像锐化研究

Image Sharpening Research Based on Improved Quantum Genetic Algorithm

针对量子遗传在锐化图像出现的缺点,提出改进方法。对量子采用自适应量子旋转门步长调整策略,不同代染色体的进化操作采用不同的旋转角步长,同代的染色体仍用同一旋转角步长进行更新,通过比较每个量子染色体的汉明距离调节其自身的进化速度;将量子染色体更新,将比较适合的染色体解在目标数值范围内判定为级别较高的染色体;对量子交叉操作采用对角线交叉方式;对图像锐化给出了算法步骤。实验仿真表明本算法在锐化边缘和抑制噪声上明显优于其他锐化方法,并且图像的边缘也得到了很好的增强。

Aiming at the problem of GQA in sharpening image, an improved QGA is proposed. An adaptive quantum revolve door step adjustment strategy is used, different rotate angles are adopted for the evolution of different generations, and the same generation still has the same length. The Hamming distance of every quantum chromosome is compared in order to adjust its evolution speed. The solutions of quantum chromosome are updated to higher grades in the target range. The diagonal crossover mode is adopted for quantum crossover operation. The flow chart of the image sharpening algorithm is given. The simulation results show that the proposed algorithm is much better than other methods in sharpening edges and reducing noise, and image edges also get a very good enhancement.