Orientation identification of the power spectrum

A novel autofocusing algorithm using the directional wavelet power spectrum is proposed for time delayed and integration charge coupled device (TDI CCD) space cameras, which overcomes the difficulty of focus measure for the real-time change of imaging scenes. Using the multiresolution and band-pass characteristics of wavelet transform to improve the power spectrum based on fast Fourier transform (FFT), the wavelet power spectrum is less sensitive to the variance of scenes. Moreover, the new focus measure can effectively eliminate the impact of image motion mismatching by the directional selection. We test the proposed method's performance on synthetic images as well as a real ground experiment for one TDI CCD prototype camera, and compare it with the focus measure based on the existing FFT spectrum. The simulation results show that the new focus measure can effectively express the defocused states for the real remote sensing images. The error ratio is only 0.112, while the prevalent algorithm based on the FFT spectrum is as high as 0.4. Compared with the FFT-based method, the proposed algorithm performs at a high reliability in the real imaging experiments, where it reduces the instability from 0.600 to 0.161. Two experimental results demonstrate that the proposed algorithm has the characteristics of good monotonicity, high sensitivity, and accuracy. The new algorithm can satisfy the autofocusing requirements for TDI CCD space cameras.

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“…Ix; y f x; y ⊗ hx; y; (15) where f x; y is the input image and hx; y is the PSF. The MTF corresponding to defocusing is the FFT of PSF.…”

Section: A Change Of Power Spectrum Caused By Defocusingmentioning

confidence: 99%

“…Nevertheless, the varying scenes, whose influence is also remarkable in TDI CCD space cameras, are not considered. To eliminate the influence of the varying scenes on the focus measure, a method based on the power spectrum has been studied, and has gotten auspicious results [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Wavelet power spectrum-based autofocusing algorithm for time delayed and integration charge coupled device space camera

et al. 2012

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“…[1][2][3][4][5][6][7][8][9][10] The image-based passive autofocus algorithms are widely studied for their high accuracy and no requirement for extra equipment. [1][2][3][4][5][6][7][8][9][10] The image-based passive autofocus algorithms are widely studied for their high accuracy and no requirement for extra equipment.…”

Section: Introductionmentioning

confidence: 99%

Analysis of image motion on autofocus precision for aerial cameras

et al. 2015

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Downloaded From: http://opticalengineering.spiedigitallibrary.org/ on 08/17/2015 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspxAbstract. Aerial cameras often suffer from image motion due to the severe aerial environments that decrease the autofocus precision. An analysis of the influence of image motion on autofocus precision is provided to obtain the optimal focus position. First, the focus measure function based on discrete Fourier transform is applied to evaluate the sharpness of the collected image for autofocusing. Then, two forms of image motion model, including linear shift and jitter, are discussed and analyzed. Finally, a quadratic fitting curve is employed on the focus measure function for image sequence. The maximum of the fitted curve corresponds to the optimal focus position. Experimental results demonstrate that the maximum value of the focus measure function decreases more than 10% approximately when the image motion increases to five pixels, and the optimal focus position computed by quadratic fitted curve generated a good performance in autofocus techniques. The proposed autofocus algorithm can be applied to aerial cameras.

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Orientation identification of the power spectrum

Cited by 2 publications

References 35 publications

Wavelet power spectrum-based autofocusing algorithm for time delayed and integration charge coupled device space camera

Wavelet power spectrum-based autofocusing algorithm for time delayed and integration charge coupled device space camera

Analysis of image motion on autofocus precision for aerial cameras

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