CAJ | 학술논문

分析了部分云覆盖的单幅光学遥感图像经过多层小波变换后,景物信息和云噪音在小波分解系数中的分布关系,并提出了云区阈值法来有效去除云噪音.通过选择适当的分界层数,将景物信息、云噪音尽可能分别分配到低层和高层细节系数中.高层细节系数中除主要包含云噪音外,也有部分有用景物信息.由于云噪音亮度大于景物,根据亮度特征合理选择高层细节系数的亮度阈值,去除云噪音,而保留其中的景物信息.通过对低层、高层细节系数和近似系数分别设置权重,增加景物对比度,减小残留云影响,从而重构得到恢复图像.提出了以信息熵作为分界层数、权重、阈值等参量选择的定量标准.实验证明,按信息熵标准能正确地选择参量,依据本文算法得到的去云效果远优越于同态滤波和Retinex算法,且能充分保留云区以外景物信息.
분석료부분운복개적단폭광학요감도상경과다층소파변환후,경물신식화운조음재소파분해계수중적분포관계,병제출료운구역치법래유효거제운조음.통과선택괄당적분계층수,장경물신식、운조음진가능분별분배도저층화고층세절계수중.고층세절계수중제주요포함운조음외,야유부분유용경물신식.유우운조음량도대우경물,근거량도특정합리선택고층세절계수적량도역치,거제운조음,이보류기중적경물신식.통과대저층、고층세절계수화근사계수분별설치권중,증가경물대비도,감소잔류운영향,종이중구득도회복도상.제출료이신식적작위분계층수、권중、역치등삼량선택적정량표준.실험증명,안신식적표준능정학지선택삼량,의거본문산법득도적거운효과원우월우동태려파화Retinex산법,차능충분보류운구이외경물신식.
Frequency relationships of wavelet coefficients describing sceneries and cloud in a single optical remote sensing image are analyzed after it is decomposed by wavelet transform.An algorithm of cloud threshold is proposed for removing cloud.Scenery information and cloud noises are distributed to coefficients of low levels and high levels respectively by choosing appropriate numbers of demarcation levels.Most of cloud noises and some scenery information are included in high level coefficients where cloud is brighter than scenery.Cloud can be removed from these coefficients and scenery information can be kept by setting a threshold with brightness.Weight factors are assigned to detail coefficients of low level,high level,and approximation coefficients respectively for enhancing the contrast of sceneries and decrease remaining cloud.The three parts of coefficients are reconstructed and fused to get processed result.Entropy is proposed to be a criterion to choose best demarcation level,weighted factor and threshold.It is proved that according to the entropy as a criterion these parameters can be chosen correctly by experiments.And the proposed algorithm is better than homomorphism filtering and Retinex algorithm.