光學(xué)遙感影像壓縮及融合的質(zhì)量評價(jià)研究
發(fā)布時(shí)間：2019-06-12 05:23
【摘要】：由于遙感衛(wèi)星成像系統(tǒng)性能、圖像壓縮算法、數(shù)據(jù)遠(yuǎn)程傳輸設(shè)備等的不完善,以及大氣層及設(shè)備噪聲等的干擾,在遙感衛(wèi)星圖像的獲取、壓縮、傳送的過程中,遙感圖像降質(zhì)和模糊失真是不可避免的。這些給遙感圖像的處理、分析、應(yīng)用帶來了很大的難度。 本文針對遙感圖像壓縮算法對比選優(yōu)中,對壓縮圖像的主觀評價(jià)及客觀評價(jià)的實(shí)際問題,以及目前國標(biāo)遙感影像圖質(zhì)量評價(jià)中,只有主觀定性描述,沒有客觀量化指標(biāo)的問題,在廣泛了解國內(nèi)外圖像質(zhì)量評價(jià)相關(guān)理論和技術(shù)的最新發(fā)展現(xiàn)狀基礎(chǔ)之上,分析和研究了遙感圖像質(zhì)量的主觀評價(jià)方法和客觀評價(jià)方法存在的問題,并探討了原始遙感影像及遙感融合影像的質(zhì)量評價(jià)的方法和思路,為進(jìn)一步的深入研究奠定了基礎(chǔ)。本文的主要研究工作如下： 一、圖像質(zhì)量主觀評價(jià)方法研究 針對遙感圖像壓縮算法上星選優(yōu)的實(shí)際問題,提出了一種新的基于Shell排序算法的圖像質(zhì)量主觀評價(jià)方法,并開發(fā)了基于該方法的遙感圖像主觀評價(jià)軟件。該方法是將Shell排序算法與已有的遙感壓縮圖像質(zhì)量的主觀評價(jià)方法中的成對比較法相結(jié)合,兼有排序方法和成對比較法的優(yōu)點(diǎn),減少了主觀評價(jià)中圖像比較的次數(shù)。利用該軟件,對924幅遙感壓縮圖像,經(jīng)過兩組遙感專業(yè)一線作業(yè)人員的主觀測評實(shí)驗(yàn),最后對實(shí)驗(yàn)結(jié)果進(jìn)行分析處理,結(jié)果表明新主觀評價(jià)方法比原有的成對比較法提高效率達(dá)38%-52%。 二、圖像質(zhì)量客觀評價(jià)方法研究 為了從客觀的角度評價(jià)遙感壓縮失真圖像的質(zhì)量,本文提出一個將圖像的梯度幅值、相位以及結(jié)構(gòu)相似度(SSIM)三者相結(jié)合的圖像質(zhì)量評價(jià)新模型—梯度相似度(GSIM)模型,以及基于該模型的圖像質(zhì)量評價(jià)算法。新模型與SSIM模型及基于梯度的模型相比,不僅包含亮度、對比度和結(jié)構(gòu)三部分信息,而且更重要的是該模型增加了梯度相位信息。通過對LIVE圖像數(shù)據(jù)庫的982幅失真圖像和924幅遙感壓縮影像的實(shí)驗(yàn),結(jié)果顯示新模型的性能優(yōu)于MSE、PSNR、SSIM等傳統(tǒng)模型以及基于梯度的模型。與SSIM等模型相比,新模型不但能較好地解決對嚴(yán)重失真圖像的客觀評價(jià)與主觀感受并不完全相符的問題,而且還能更好地處理對多種類型失真圖像的混合評價(jià)效果較差的問題。 三、遙感影像產(chǎn)品的構(gòu)象質(zhì)量評價(jià)研究 針對遙感影像平面圖制作規(guī)范國標(biāo)(GBT15968-2008)中,對影像質(zhì)量評定標(biāo)準(zhǔn),只有主觀定性描述(“層次豐富、清晰易讀、色調(diào)均勻,反差適中”),而無客觀定量的評價(jià)指標(biāo)的問題。對于圖像的層次、清晰度、輻射、反差、信噪比等方面的表達(dá)和評價(jià)問題,本文從亮度、對比度、信息量、清晰度、紋理信息及空間細(xì)節(jié)的角度進(jìn)行分析,分別給出相應(yīng)的客觀評價(jià)指標(biāo)。對于圖像對比度反差適中的主觀定性描述,在深入研究人眼視覺特性的基礎(chǔ)上,提出了一種的基于高斯正態(tài)函數(shù)加權(quán)的對比度評價(jià)指標(biāo),用該指標(biāo)表示反差適中,比標(biāo)準(zhǔn)差更符合人的視覺感受,最后用實(shí)驗(yàn)驗(yàn)證新模型指標(biāo)的有效性。 四、遙感影像融合及其質(zhì)量評價(jià)研究 本文針對遙感影像生產(chǎn)單位實(shí)際對遙感影像融合算法的選擇問題,詳細(xì)比較了現(xiàn)有的10種遙感影像融合算法,研究了各種融合算法的基本原理,通過各種圖像質(zhì)量評價(jià)指標(biāo),分析了各種融合算法的特點(diǎn),最后提出了一般遙感影像構(gòu)象質(zhì)量的評價(jià)體系,將遙感影像的構(gòu)象質(zhì)量分解為亮度、對比度、清晰度、信息量、光譜信息、紋理信息、信噪比等幾方面因素來分別考慮,并在現(xiàn)有客觀指標(biāo)深入研究的基礎(chǔ)上,對上述各方面都給出了具體的客觀評價(jià)指標(biāo)。
[Abstract]:In the process of acquisition, compression and transmission of remote sensing satellite images, remote sensing image degradation and fuzzy distortion are inevitable due to the imperfections of remote sensing satellite imaging system performance, image compression algorithm, data remote transmission equipment and the like, as well as the interference of the atmosphere and equipment noise. The processing, analysis and application of these remote sensing images bring great difficulty. In this paper, based on the comparison of remote sensing image compression algorithms, the actual problems of the subjective evaluation and objective evaluation of the compressed image, as well as the current national standard remote sensing image quality evaluation, are only the subjective description, and there is no objective quantitative index. On the basis of a wide understanding of the latest development of the relevant theories and techniques of image quality evaluation at home and abroad, the paper analyzes and studies the subjective evaluation method and objective evaluation method of the remote sensing image quality. In this paper, the method and thought of the quality evaluation of the original remote sensing image and the remote sensing fusion image are discussed, and the basis of further research is laid. The main research work of this paper is as follows: Next: subjective evaluation of image quality In this paper, a new image quality master based on shell sort algorithm is proposed in order to solve the practical problem of the satellite selection on the remote sensing image compression algorithm. The method of view evaluation is developed and a remote sensing image master based on the method is developed. The method is combined with the paired comparison method in the subjective evaluation method of the quality of the existing remote sensing compressed image, and has the advantages of the sorting method and the comparison method, so that the image in the subjective evaluation is reduced, The results show that the new subjective evaluation method is more efficient than that of the former one, and the result shows that the new subjective evaluation method is more efficient than the original one. % -52%.2, Image quality In order to evaluate the quality of the remote sensing compression distortion image from an objective point of view, an objective evaluation method is presented in this paper. a new model of image quality evaluation based on the combination of gradient magnitude, phase, and structure similarity (SSIM) of the image is used to evaluate the gradient similarity (GSIM) model of the new model, and based on the model, Compared with the SSIM model and the gradient-based model, the new model not only contains three parts of the brightness, the contrast and the structure, but also the model The results show that the performance of the new model is better than that of MSE, PSNR, SSIM and other traditional models. Compared with the SSIM and other models, the new model can not only solve the problem that the objective evaluation of the serious distorted image is not completely consistent with the subjective feeling, but also can better deal with the mixing of many types of distorted images. the problem of poor evaluation.3. Remote sensing image In the national standard (GBT15968-2008), the study on the conformation quality of the product has only a subjective description ("The level is rich, clear and easy to read, the tone is uniform, the contrast is moderate") for the standard of image quality assessment (GBT15968-2008). There is no objective and quantitative evaluation index. For the expression and evaluation of the level, definition, radiation, contrast and signal-to-noise ratio of the image, this paper analyzes the angle of brightness, contrast, information amount, definition, texture information and spatial detail. The objective evaluation index is given respectively. Based on the study of the visual characteristics of the human eye, a kind of contrast evaluation index based on the Gaussian positive state function weighting is proposed based on the study of the visual characteristics of the human eye. The contrast is moderate. The specific standard deviation is more in line with the human visual sense, and finally, The experiment verifies the effectiveness of the new model index. In this paper, the remote sensing image fusion and its quality evaluation are studied in this paper. In this paper, the selection of the remote sensing image fusion algorithm for remote sensing image production units is studied in this paper, and the existing 10 remote sensing image fusion is compared in detail. In this paper, the basic principle of various fusion algorithms is studied, the characteristics of various fusion algorithms are analyzed through various image quality evaluation indexes, and finally the evaluation system of the constellation quality of the general remote sensing image is put forward, and the conformation quality of the remote sensing image is decomposed into the brightness and the contrast, The definition, information amount, spectral information, texture information, signal-to-noise ratio and the like are taken into consideration respectively, and on the basis of the in-depth study of the existing objective indexes, the invention
【學(xué)位授予單位】：武漢大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TP751
本文編號：2497774
[Abstract]:In the process of acquisition, compression and transmission of remote sensing satellite images, remote sensing image degradation and fuzzy distortion are inevitable due to the imperfections of remote sensing satellite imaging system performance, image compression algorithm, data remote transmission equipment and the like, as well as the interference of the atmosphere and equipment noise. The processing, analysis and application of these remote sensing images bring great difficulty. In this paper, based on the comparison of remote sensing image compression algorithms, the actual problems of the subjective evaluation and objective evaluation of the compressed image, as well as the current national standard remote sensing image quality evaluation, are only the subjective description, and there is no objective quantitative index. On the basis of a wide understanding of the latest development of the relevant theories and techniques of image quality evaluation at home and abroad, the paper analyzes and studies the subjective evaluation method and objective evaluation method of the remote sensing image quality. In this paper, the method and thought of the quality evaluation of the original remote sensing image and the remote sensing fusion image are discussed, and the basis of further research is laid. The main research work of this paper is as follows: Next: subjective evaluation of image quality In this paper, a new image quality master based on shell sort algorithm is proposed in order to solve the practical problem of the satellite selection on the remote sensing image compression algorithm. The method of view evaluation is developed and a remote sensing image master based on the method is developed. The method is combined with the paired comparison method in the subjective evaluation method of the quality of the existing remote sensing compressed image, and has the advantages of the sorting method and the comparison method, so that the image in the subjective evaluation is reduced, The results show that the new subjective evaluation method is more efficient than that of the former one, and the result shows that the new subjective evaluation method is more efficient than the original one. % -52%.2, Image quality In order to evaluate the quality of the remote sensing compression distortion image from an objective point of view, an objective evaluation method is presented in this paper. a new model of image quality evaluation based on the combination of gradient magnitude, phase, and structure similarity (SSIM) of the image is used to evaluate the gradient similarity (GSIM) model of the new model, and based on the model, Compared with the SSIM model and the gradient-based model, the new model not only contains three parts of the brightness, the contrast and the structure, but also the model The results show that the performance of the new model is better than that of MSE, PSNR, SSIM and other traditional models. Compared with the SSIM and other models, the new model can not only solve the problem that the objective evaluation of the serious distorted image is not completely consistent with the subjective feeling, but also can better deal with the mixing of many types of distorted images. the problem of poor evaluation.3. Remote sensing image In the national standard (GBT15968-2008), the study on the conformation quality of the product has only a subjective description ("The level is rich, clear and easy to read, the tone is uniform, the contrast is moderate") for the standard of image quality assessment (GBT15968-2008). There is no objective and quantitative evaluation index. For the expression and evaluation of the level, definition, radiation, contrast and signal-to-noise ratio of the image, this paper analyzes the angle of brightness, contrast, information amount, definition, texture information and spatial detail. The objective evaluation index is given respectively. Based on the study of the visual characteristics of the human eye, a kind of contrast evaluation index based on the Gaussian positive state function weighting is proposed based on the study of the visual characteristics of the human eye. The contrast is moderate. The specific standard deviation is more in line with the human visual sense, and finally, The experiment verifies the effectiveness of the new model index. In this paper, the remote sensing image fusion and its quality evaluation are studied in this paper. In this paper, the selection of the remote sensing image fusion algorithm for remote sensing image production units is studied in this paper, and the existing 10 remote sensing image fusion is compared in detail. In this paper, the basic principle of various fusion algorithms is studied, the characteristics of various fusion algorithms are analyzed through various image quality evaluation indexes, and finally the evaluation system of the constellation quality of the general remote sensing image is put forward, and the conformation quality of the remote sensing image is decomposed into the brightness and the contrast, The definition, information amount, spectral information, texture information, signal-to-noise ratio and the like are taken into consideration respectively, and on the basis of the in-depth study of the existing objective indexes, the invention
【學(xué)位授予單位】：武漢大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TP751
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