本文選題：CMOS相機 + Karhunen-Loeve變換　； 參考：《中國科學(xué)院研究生院(長春光學(xué)精密機械與物理研究所)》2016年博士論文

【摘要】：由于空間相機在視頻分辨率以及幀頻等指標(biāo)要求的不斷提高,導(dǎo)致CMOS輸出的視頻數(shù)據(jù)量急劇增加�，F(xiàn)有的壓縮算法運算過程十分復(fù)雜,而且主要停留在軟件仿真階段,硬件實現(xiàn)困難且效果較差。為了有效緩解星上存儲器以及信道傳輸?shù)膲毫?研制出壓縮性能好、數(shù)據(jù)處理快的實時視頻壓縮系統(tǒng)迫在眉睫。論文以參與的工程項目“空間CMOS相機技術(shù)”項目為背景,對全色和多譜段CMOS相機視頻壓縮技術(shù)分別進(jìn)行了研究�，F(xiàn)將本文的主要研究內(nèi)容和成果概括如下：1、根據(jù)項目需求以及CMOS視頻的特點,探討小型CMOS相機及高分辨率CMOS相機ASIC的ADV212壓縮技術(shù)。提出利用Custom-specific工作模式為各種格式的視頻提供接口,并通過FPGA內(nèi)部的塊RAM以及DDR3 SDRAM的乒乓操作對數(shù)據(jù)進(jìn)行緩存,顯著地提高了工作效率;之后,為了適用于不同應(yīng)用場合,本文方法實現(xiàn)了碼流的存儲后傳輸以及直接傳輸之間的切換,并通過糾錯編碼極大的提升了閃存的糾錯能力；最后,為了驗證方法的可行性,本文基于壓縮板以及解壓板進(jìn)行了實驗驗證。結(jié)果表明,壓縮系統(tǒng)可實現(xiàn)實時穩(wěn)定的工作,通過軟件設(shè)置,系統(tǒng)可以實現(xiàn)極高的壓縮比,壓縮比80：1時,平均峰值信噪比(PSNR)高于28 dB,壓縮比150：1時,平均PSNR高于26 dB,解決了在大數(shù)據(jù)量下,壓縮系統(tǒng)硬件實現(xiàn)困難以及實時傳輸困難等問題。2、結(jié)合離散小波變換(Discrete Wavelet Transform, DWT)與Karhunen-Loeve變換(KLT)提出一種空間多光譜視頻壓縮算法。通過兩種變換的有效結(jié)合可以將圖像的能量集中到少數(shù)系數(shù)上,更好地達(dá)到壓縮效果。本文首先將多光譜圖像的每個譜段進(jìn)行快速2維離散5/3小波變換,消除多光譜圖像的大部分空間冗余。然后對所有譜段產(chǎn)生的小波系數(shù)進(jìn)行改進(jìn)KL變換,來消除光譜冗余和殘存的空間冗余。最后對所得系數(shù)進(jìn)行熵編碼,得到壓縮碼流。實驗結(jié)果表明,在0.25-2bit/pixel (b/p)范圍內(nèi),平均PSNR達(dá)到41dB,與其他多光譜圖像壓縮算法相比,極大的提高了系統(tǒng)PSNR,提升了多光譜圖像壓縮算法的性能；同時提出了硬件實現(xiàn)策略,驗證了本文理論的正確性以及算法的可行性,為空間多光譜圖像壓縮系統(tǒng)實現(xiàn)提供了參考。3、圖像進(jìn)行KLT和一級DWT后,不同譜段的系數(shù)之間以及同一譜段的高頻子帶之間仍然存在很大的相關(guān)性,其平均值大于0.9,提高小波變換級數(shù)后此值會相應(yīng)的降低,但效果不是十分理想；基于DWT和Tucker分解的壓縮算法將圖像作為張量,這樣能完整的表示高維數(shù)據(jù)并保持其本征結(jié)構(gòu),較好的去除圖像的空間冗余和光譜冗余,但稀疏表示不足,達(dá)不到更高的壓縮比。本算法的提出可以很好的克服以上兩種方法的不足,在保證較高壓縮性能的同時,有效地保護(hù)了光譜信息。首先將多光譜圖像的所有譜段進(jìn)行KLT,消除多光譜圖像的光譜冗余。然后將變換后的每個譜段進(jìn)行2維離散9/7小波變換,消除多光譜圖像的空間冗余。其次,將變換后的每個小波子帶都看作非負(fù)張量,對其進(jìn)行Tucker分解(Tucker Decomposition, TD),并用阻尼高斯-牛頓算法(damped Gauss-Newton, dGN)求出最優(yōu)解,進(jìn)一步消除光譜冗余和空間殘余冗余。最后,將得到的模式矩陣和核心張量進(jìn)行熵編碼。在壓縮比4：1-32：1范圍內(nèi),平均PSNR高于43dB,與其他多光譜圖像壓縮算法相比,極大的提高了系統(tǒng)PSNR,提升了多光譜圖像壓縮算法的性能。4、采用MT9V032型CMOS數(shù)字圖像傳感器設(shè)計了一款完整的小型化、低功耗相機�；诔跫壪癫罾碚撛O(shè)計了焦距為12.95 mm,F數(shù)為5的光學(xué)系統(tǒng),該系統(tǒng)體積小、結(jié)構(gòu)緊湊,在空間頻率83 lp/mm處,各視場調(diào)制傳遞函數(shù)(MTF)均優(yōu)于0.5；電子學(xué)系統(tǒng)以FPGA作為時序控制平臺,控制CMOS輸出數(shù)字視頻信號,數(shù)字視頻信號通過差分芯片以低壓差分信號(LVDS)格式輸出到圖像采集卡,最后在計算機上成像。實驗結(jié)果表明,本文設(shè)計的相機像質(zhì)良好、功耗低、移植性強、可靠性高,時鐘為26.6 MHz時,幀頻為60幀/秒,并可通過調(diào)節(jié)內(nèi)部寄存器的值實現(xiàn)多種模式,特別適用于對相機體積以及成像質(zhì)量要求較高的場合。5、根據(jù)高分辨率空間CMOS相機視頻壓縮系統(tǒng)指標(biāo),設(shè)計了用于大、中型視頻壓縮系統(tǒng)的基于KAC-06040的CMOS相機系統(tǒng)。設(shè)計的焦距為1175mm,F數(shù)為6.71的光學(xué)系統(tǒng),該系統(tǒng)體積小、結(jié)構(gòu)緊湊,在空間頻率106.41 lp/mm處,各視場MTF均優(yōu)于0.446(有遮攔),能量集中度11um以內(nèi)的能量集中度均優(yōu)于80%;電子學(xué)系統(tǒng)以FPGA作為時序控制平臺,控制CMOS輸出數(shù)字視頻信號,數(shù)字視頻信號通過Camera Link傳輸線以Medium模式輸出到圖像采集卡,最后在計算機上成像。實驗結(jié)果表明,本文設(shè)計的相機像質(zhì)良好、功耗低、移植性強、可靠性高,滿足項目需求。
[Abstract]:Because of the continuous improvement of the spatial camera in the video resolution and frame rate, the amount of video data in the CMOS output has increased dramatically. The operation process of the existing compression algorithm is very complex, and it is mainly in the software simulation stage. The hardware implementation is difficult and the effect is poor. It is effective to alleviate on the satellite memory and channel transmission. In order to develop a real-time video compression system with good compression performance and fast data processing, the paper studies the video compression technology of all color and multispectral CMOS cameras in the background of the project "space CMOS camera technology" involved in the project. The main contents and results of this paper are summarized as follows: 1, the root of this paper is as follows According to the requirements of the project and the features of CMOS video, the ADV212 compression technology of the small CMOS camera and the high resolution CMOS camera ASIC is discussed. It is proposed to use the Custom-specific working mode to provide the video interface for various formats, and to cache the data through the table operation of the block RAM in FPGA and the DDR3 SDRAM in the FPGA, which significantly improves the work efficiency. In order to apply to different applications, in order to apply to different applications, this method realizes the transfer of the memory after the storage and the transfer between direct transmission, and improves the error correction ability of the flash memory greatly by error correction coding. Finally, in order to verify the feasibility of the method, this paper is based on the compression plate and the decompression board. The system can achieve real-time and stable work. Through the software setting, the system can achieve high compression ratio. When the compression ratio 80:1, the average peak signal to noise ratio (PSNR) is higher than 28 dB. When the compression ratio is 150:1, the average PSNR is higher than 26 dB. It solves the problem of hard parts of the compression system and the difficulty of real-time transmission under the large amount of data. A spatial multi spectral video compression algorithm is proposed by Discrete Wavelet Transform (DWT) and Karhunen-Loeve transform (KLT). Through the effective combination of two kinds of transform, the energy of the image can be concentrated to a few coefficients, and the compression effect is better. First, each spectrum segment of the multi spectral image is fast 2 dimensional discrete. 5/3 wavelet transform eliminates most of the spatial redundancy of multispectral images. Then, the wavelet coefficients generated by all spectral segments are modified to eliminate the spectral redundancy and residual spatial redundancy. Finally, the entropy coding of the obtained coefficients is used to obtain the compressed code stream. The experimental results show that the average PSNR reaches 41D within the range of 0.25-2bit/pixel (b/p). B, compared with other multi spectral image compression algorithms, it greatly improves the system PSNR and improves the performance of the multi spectral image compression algorithm. At the same time, the hardware implementation strategy is proposed to verify the correctness of the theory and the feasibility of the algorithm. It provides a reference.3 for the realization of the spatial multi spectral image compression system, the image is KLT and the first level D. After WT, there is still a great correlation between the coefficients of the different spectral segments and the high frequency subbands of the same spectral section. The average value is greater than 0.9. The value will be reduced accordingly, but the effect is not very ideal. The compression algorithm based on DWT and Tucker decomposes the image as a tensor, so that the high dimension can be expressed in a complete dimension. The data and its eigenstructure are maintained to better remove the spatial redundancy and spectral redundancy of the image, but the sparse representation is insufficient and can not reach the higher compression ratio. The proposed algorithm can overcome the shortcomings of the above two methods, and effectively protect the spectral information while ensuring high compression performance. The spectral section is KLT to eliminate the spectral redundancy of the multispectral image. Then each spectral segment after the transformation is divided into 2 dimensional discrete 9/7 wavelet transform to eliminate the spatial redundancy of the multispectral image. Secondly, each wavelet subband after transformation is regarded as a non negative tensor and Tucker decomposition (Tucker Decomposition, TD) is applied to it, and the damping Gauss Newton calculation is used. The optimal solution is obtained by the method (damped Gauss-Newton, dGN) to further eliminate spectral redundancy and space residual redundancy. Finally, the obtained pattern matrix and core tensor are entropy coded. The average PSNR is higher than 43dB in the range of compression ratio 4:1-32:1. Compared with other multispectral image compression algorithms, the system PSNR is greatly improved and the multi light is enhanced. The performance of the spectral image compression algorithm is.4. A complete miniaturized and low power consumption camera is designed by using MT9V032 CMOS digital image sensor. Based on the primary aberration theory, the optical system with a focal length of 12.95 mm and a F number of 5 is designed. The system is small in size and compact in structure. The field modulation transfer function (MTF) is superior to all field modulation transfer functions (MTF) at the space frequency rate of 83 lp/mm. 0.5, the electronic system uses FPGA as the timing control platform to control the CMOS output digital video signal. The digital video signal is output to the image acquisition card in the low voltage differential signal (LVDS) format through the differential chip, and finally is imaging on the computer. The experimental results show that the camera designed in this paper has good image quality, low power consumption, strong portability and high reliability. When the clock is 26.6 MHz, the frame rate is 60 frames per second, and many modes can be realized by adjusting the value of the internal registers. It is especially suitable for the situation of.5 with high camera volume and high imaging quality. According to the index of the video compression system of the high resolution space CMOS camera, a KAC-06040 based CMOS for large and medium video compression system is designed. Camera system. The optical system with a focal length of 1175mm and a F number of 6.71 is designed. The system is small in size and compact in structure. At the space frequency of 106.41 lp/mm, the MTF of each field of view is better than 0.446. The energy concentration within 11um of the energy concentration is better than 80%; the electronic system uses FPGA as the timing control platform to control the CMOS output digital video. The signal, the digital video signal is output to the image acquisition card by the Medium mode through the Camera Link transmission line, and finally is imaging on the computer. The experimental results show that the camera designed in this paper has good quality, low power consumption, strong portability and high reliability, and meets the requirements of the project.

【學(xué)位授予單位】：中國科學(xué)院研究生院(長春光學(xué)精密機械與物理研究所)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：TP391.41

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