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黄淮学院 信息工程学院, 河南 驻马店 463000
收稿日期:2015-01-26,
修回日期:2015-03-14,
纸质出版日期:2015-06-05
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周原, 张韧志. 基于量子免疫蛙跳算法的图像增强研究[J]. 液晶与显示, 2015,30(3): 499-504
ZHOU Yuan, ZHANG Ren-zhi. Image enhancement research based on quantum immune leap frog[J]. , 2015,30(3): 499-504
周原, 张韧志. 基于量子免疫蛙跳算法的图像增强研究[J]. 液晶与显示, 2015,30(3): 499-504 DOI: 10.3788/YJYXS20153003.0499.
ZHOU Yuan, ZHANG Ren-zhi. Image enhancement research based on quantum immune leap frog[J]. , 2015,30(3): 499-504 DOI: 10.3788/YJYXS20153003.0499.
针对图像增强的特点
提出量子免疫蛙跳算法.该算法按适应度大小排序的青蛙个体进行量子编码
同时蛙跳移动离散化;通过动态调整量子蛙跳旋转门实现量子染色体中所有的量子比特都朝着与最优解对应的量子比特基态动态优化偏转;采用Hadamard门对量子位变异
基于阴性选择算法对蛙跳免疫进行像素匹配
并给出了图像增强过程.实验仿真表明
本文算法对图像增强效果的轮廓和细节更加清晰
层次感强
结构相似性SSIM其值较好
为0.9849.
According to the characteristic of image enhancement
quantum immune frog leap algorithm is proposed. Frog individuals were quantum-encoded by this algorithm according to the order of fitness degree
meanwhile
the leap frog movements were discretized. Through the dynamic adjustment of the revolving gate of quantum leapfrog
all quantum bits of the quantum chromosome were deflected towards the dynamic optimization of the ground state of quantum bits which were corresponded to the optimal solution. Qubits were mutated by adopting Hadamard gate
the leap frog immunization was pixel-matched based on the feminine selection algorithm
and image enhancement process was provided. The experimental result show that effect of outline and details of QILF is more clearly
the better SSIM is 0.984 9.
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