现代电子技术
現代電子技術
현대전자기술
MODERN ELECTRONICS TECHNIQUE
2014年
3期
55-60
,共6页
遥感图像%图像融合%PCNN模型%HSV彩色空间
遙感圖像%圖像融閤%PCNN模型%HSV綵色空間
요감도상%도상융합%PCNN모형%HSV채색공간
remote sensing image%image fusion%PCNN model%HSV color space
介绍了PCNN模型原理,提出了基于双通道自适应的PCNN多光谱与全色图像融合算法。该算法首先将RGB空间的多光谱图像转换为HSV彩色空间,然后将HSV彩色空间中的非彩色通道(V通道)的灰度像素值和全色图像的像素灰度值分别作为PCNN-1及PCNN-2的神经元输入,利用方向性信息作为自适应链接强度系数,对非彩色通道图像和全色图像进行自适应分解,再将点火时间序列送入判决因子得到新的非彩色通道图像,最后将原多光谱图像的H通道分量、S通道分量及新的V通道分量经HSV空间逆变换获得最终的融合图像。实验结果表明,该算法不仅解决了链接强度系数自动设置的问题,而且充分考虑到图像边缘和方向特征的影响,无论在主观视觉效果,还是客观评价标准上均优于IHS、PCA、小波融合等其他图像融合算法,同时降低了计算复杂度。
介紹瞭PCNN模型原理,提齣瞭基于雙通道自適應的PCNN多光譜與全色圖像融閤算法。該算法首先將RGB空間的多光譜圖像轉換為HSV綵色空間,然後將HSV綵色空間中的非綵色通道(V通道)的灰度像素值和全色圖像的像素灰度值分彆作為PCNN-1及PCNN-2的神經元輸入,利用方嚮性信息作為自適應鏈接彊度繫數,對非綵色通道圖像和全色圖像進行自適應分解,再將點火時間序列送入判決因子得到新的非綵色通道圖像,最後將原多光譜圖像的H通道分量、S通道分量及新的V通道分量經HSV空間逆變換穫得最終的融閤圖像。實驗結果錶明,該算法不僅解決瞭鏈接彊度繫數自動設置的問題,而且充分攷慮到圖像邊緣和方嚮特徵的影響,無論在主觀視覺效果,還是客觀評價標準上均優于IHS、PCA、小波融閤等其他圖像融閤算法,同時降低瞭計算複雜度。
개소료PCNN모형원리,제출료기우쌍통도자괄응적PCNN다광보여전색도상융합산법。해산법수선장RGB공간적다광보도상전환위HSV채색공간,연후장HSV채색공간중적비채색통도(V통도)적회도상소치화전색도상적상소회도치분별작위PCNN-1급PCNN-2적신경원수입,이용방향성신식작위자괄응련접강도계수,대비채색통도도상화전색도상진행자괄응분해,재장점화시간서렬송입판결인자득도신적비채색통도도상,최후장원다광보도상적H통도분량、S통도분량급신적V통도분량경HSV공간역변환획득최종적융합도상。실험결과표명,해산법불부해결료련접강도계수자동설치적문제,이차충분고필도도상변연화방향특정적영향,무론재주관시각효과,환시객관평개표준상균우우IHS、PCA、소파융합등기타도상융합산법,동시강저료계산복잡도。
The principle of PCNN model is introduced,and an image fusion algorithm of multispectral and panchromatic based on adaptive dual-channel PCNN is proposed. Firstly the multispectral image of RGB space is converted to HSV color space,and then the gray level of achromatic channel(channel V)in HSV color space and gray level of panchromatic images are entered as PCNN-1 and PCNN-2 neurons respectively,using orientation information as an adaptive link strength factor to achieve adaptive decomposition for achromatic channel and panchromatic images. The duration of ignition sequence is sent to judgment factor to get new of achromatic channel image. Finally the final fused image is obtained through HSV space inverse transformation of H channel component,S Channel component and new V-channel component of original multispectral image. Ex-perimental results show that the algorithm not only solved the problem of automatically setting linking strength factor,but also took full account of the effect of image edge and directional characteristics. No matter the subjective visual effect,or objective evaluation standards they are all better than other image fusion algorithms such as IHS,PCA,wavelet transform image fusion, the computational complexity is reduced in the meantime.