CAJ | 학술논문

针对遥感图像主观评价方法的低效率以及常用客观评价方法无法充分考虑人眼对图像的感知特性的问题，文章提出了一种基于支持向量机的无参考遥感图像质量（quality）评价方法。首先建立遥感图像主观评价库，然后在不需要图像失真信息的基础上，利用支持向量机（SVM）将图像的失真类型分为三类，并对每类进行单项评价，再通过加权得到遥感图像的总评分，最后将本文方法、信噪比与信息熵的评价结果回归到主观评价空间并进行对比。实验证明，文章所提方法能客观地评价遥感图像的质量，且优于信噪比和信息熵两种质量评价方法，其结果与人眼视觉感受相符。
침대요감도상주관평개방법적저효솔이급상용객관평개방법무법충분고필인안대도상적감지특성적문제，문장제출료일충기우지지향량궤적무삼고요감도상질량（quality）평개방법。수선건립요감도상주관평개고，연후재불수요도상실진신식적기출상，이용지지향량궤（SVM）장도상적실진류형분위삼류，병대매류진행단항평개，재통과가권득도요감도상적총평분，최후장본문방법、신조비여신식적적평개결과회귀도주관평개공간병진행대비。실험증명，문장소제방법능객관지평개요감도상적질량，차우우신조비화신식적량충질량평개방법，기결과여인안시각감수상부。
In view of low efficiency of subjective assessment method for remote sensing image and lack of full consideration of human eye perception of common objective assessment method for the image features, this paper proposes a no-reference remote sensing image quality assessment method based on support vector machine. Firstly, a subjective assessment library for remote sensing image is established, and then,without image distortion information, we use support vector machine to classify image distortion into three categories, and compute individual evaluation for each category. The final remote sensing image quality is obtained by probability-weighted summation. Finally, the results of the method proposed by the paper, the signal-to-noise ratio and the information entropy are regressed back to the subjective assessment space and compared. In the paper, the proposed method is demonstrated a good objective assessment method of remote sensing image quality, and this method is superior to the assessment methods of signal-to-noise ratio and the information entropy, whose consistent with human visual experience.