航天返回与遥感
航天返迴與遙感
항천반회여요감
SPACECRAFT RECOVERY & REMOTE SENSING
2014年
4期
81-89
,共9页
调制传递函数补偿%图像复原%空域卷积%调制传递函数%航天遥感
調製傳遞函數補償%圖像複原%空域捲積%調製傳遞函數%航天遙感
조제전체함수보상%도상복원%공역권적%조제전체함수%항천요감
modulation transfer function compensation%image restoration%spatial convolution%modulation transfer function%space remote sensing
遥感图像在成像过程中受到大气、光学系统、探测器、平台运动和电路等因素的影响,引起图像退化,图像复原算法可以改善遥感图像像质,提高图像信息的解译能力。文章介绍了调制传递函数补偿(modulation transfer function compensation,MTFC)算法的原理,从遥感成像的链路环节出发,分析了MTFC的原理,提出了一种星上实时遥感图像MTFC复原算法。通过卷积系数和抑噪参数的优化设计,在提高图像清晰度的同时能较好地抑制噪声;对不同卷积和抑噪参数的图像复原效果进行了对比,从主观和客观两个方面对复原图像进行了评价。实验结果表明,该算法能有效提高图像像质,增强图像的高频部分,采用不同类型的卫星遥感图像验证了算法的适应性。
遙感圖像在成像過程中受到大氣、光學繫統、探測器、平檯運動和電路等因素的影響,引起圖像退化,圖像複原算法可以改善遙感圖像像質,提高圖像信息的解譯能力。文章介紹瞭調製傳遞函數補償(modulation transfer function compensation,MTFC)算法的原理,從遙感成像的鏈路環節齣髮,分析瞭MTFC的原理,提齣瞭一種星上實時遙感圖像MTFC複原算法。通過捲積繫數和抑譟參數的優化設計,在提高圖像清晰度的同時能較好地抑製譟聲;對不同捲積和抑譟參數的圖像複原效果進行瞭對比,從主觀和客觀兩箇方麵對複原圖像進行瞭評價。實驗結果錶明,該算法能有效提高圖像像質,增彊圖像的高頻部分,採用不同類型的衛星遙感圖像驗證瞭算法的適應性。
요감도상재성상과정중수도대기、광학계통、탐측기、평태운동화전로등인소적영향,인기도상퇴화,도상복원산법가이개선요감도상상질,제고도상신식적해역능력。문장개소료조제전체함수보상(modulation transfer function compensation,MTFC)산법적원리,종요감성상적련로배절출발,분석료MTFC적원리,제출료일충성상실시요감도상MTFC복원산법。통과권적계수화억조삼수적우화설계,재제고도상청석도적동시능교호지억제조성;대불동권적화억조삼수적도상복원효과진행료대비,종주관화객관량개방면대복원도상진행료평개。실험결과표명,해산법능유효제고도상상질,증강도상적고빈부분,채용불동류형적위성요감도상험증료산법적괄응성。
Due to the effects of atmosphere, optical system, detector, platform motion, circuit etc, remote sensing images are degenerated. Image restoration algorithm can improve image quality and interpretation capability. This paper analyzes the domestic research on modulation transfer function compensation(MTFC)algorithms, and performs appropriate compensation after obtaining the MTF curve of the image. Based on this, starting from the link of remote sensing system, the paper introduces an onboard real-time MTFC remote sensing image restoration algorithm by briefly analyzing the theory of MTFC. The quality of resultant image is improved and the noise is limited properly by optimizing the convolution modulus and anti-noise parameter. The image restoration effects are compared for different convolution modulus and anti-noise parameters from the subjective and objective aspect. The experimental results indicate that this algorithm can effectively improve the image quality and enhance high frequency information. Moreover, the algorithm is adaptive to different types of remote sensing images.