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October 2012

Volume 51, Issue 10 (partial)

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Regression analysis in modeling of air surface temperature and factors affecting its value in Peninsular Malaysia

Jasim Mohammed Rajab, Mohd. Zubir Mat Jafri, Hwee San Lim, and Khiruddin Abdullah

Opt. Eng. 51, 101702 (May 21, 2012); http://dx.doi.org/10.1117/1.OE.51.10.101702

Online Publication Date: May 21, 2012

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This study encompasses air surface temperature (AST) modeling in the lower atmosphere. Data of four atmosphere pollutant gases (CO, O3, CH4, and H2Ovapor) dataset, retrieved from the National Aeronautics and Space Administration Atmospheric Infrared Sounder (AIRS), from 2003 to 2008 was employed to develop a model to predict AST value in the Malaysian peninsula using the multiple regression method. For the entire period, the pollutants were highly correlated (R = 0.821) with predicted AST. Comparisons among five stations in 2009 showed close agreement between the predicted AST and the observed AST from AIRS, especially in the southwest monsoon (SWM) season, within 1.3 K, and for in situ data, within 1 to 2 K. The validation results of AST with AST from AIRS showed high correlation coefficient (R = 0.845 ?startto end?0.918), indicating the model’s efficiency and accuracy. Statistical analysis in terms of β showed that H2Ovapor (0.565 to 1.746) tended to contribute significantly to high AST values during the northeast monsoon season. Generally, these results clearly indicate the advantage of using the satellite AIRS data and a correlation analysis study to investigate the impact of atmospheric greenhouse gases on AST over the Malaysian peninsula. A model was developed that is capable of retrieving the Malaysian peninsulan AST in all weather conditions, with total uncertainties ranging between 1 and 2 K.

Universal strategy for surveillance video defogging

Bin Xie, Fan Guo, and Zixing Cai

Opt. Eng. 51, 101703 (May 18, 2012); http://dx.doi.org/10.1117/1.OE.51.10.101703

Online Publication Date: May 18, 2012

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We present a new approach to remove haze from surveillance video sequences. This approach extracts the background image through the frame differential method, uses the dark channel prior to estimate the atmospheric light, and then calculates a universal transmission map on the intensity component of the background image through a process of multiscale retinex, parameter adjustment, bilateral filtering, and total variation denoising filtering. Finally, it renders haze-free video according to the haze image model. The main advantage of the proposed approach is its speed as this approach adopts a “universal strategy” that applies the same atmospheric light and a universal pseudo-transmission map to a series of video frames. Experiments demonstrate that our method produces visually pleasing defogging results and tends to preserve main details better than previous techniques. A comparative study and quantitative evaluation show the efficiency of the proposed method.

Technique for simulating anisoplanatic image formation over long horizontal paths

Jeremy P. Bos and Michael C. Roggemann

Opt. Eng. 51, 101704 (May 15, 2012); http://dx.doi.org/10.1117/1.OE.51.10.101704

Online Publication Date: May 15, 2012

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The presence of turbulence over horizontal imaging paths severely reduces the resolution available to imaging systems and introduces anisoplanatic distortions in the image frame. A variety of image processing techniques are being developed which can mitigate these effects, and sequences of high-fidelity images created via simulation are useful in their development. In this paper, we describe a simplification of the split-step wave propagation method that employs a series of uniformly spaced phase screens to accurately simulate turbulence effects on imaging over horizontal paths. Employing this method, a series of 1000 image frames were generated for each of three turbulence conditions. The mean squared error in intensity per pixel is also evaluated for each frame in comparison to a diffraction-limited reference. Examination of the per-frame intensity error statistics indicate these errors are log-normally distributed about a mean value that increases approximately linearly with turbulence strength.

Demonstration of portable solar adaptive optics system

Deqing Ren and Bing Dong

Opt. Eng. 51, 101705 (May 22, 2012); http://dx.doi.org/10.1117/1.OE.51.10.101705

Online Publication Date: May 22, 2012

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Solar-adaptive optics (AO) are more challenging than night-time AO, in some aspects. A portable solar adaptive optics (PSAO) system featuring compact physical size, low cost, and good performance has been proposed and developed. PSAO can serve as a visiting instrument for any existing ground-based solar telescope to improve solar image quality by replacing just a few optical components. High-level programming language, LabVIEW, is used to develop the wavefront sensing and control software, and general purpose computers are used to drive the whole system. During October 2011, the feasibility and good performance of PSAO was demonstrated with the 61-cm solar telescope at San Fernando Observatory. The image contrast and resolution are noticeably improved after AO correction.

Multi-resolution remote sensing image registration using differential evolution with adaptive strategy selection

Zhenbang Hu, Wenyin Gong, and Zhihua Cai

Opt. Eng. 51, 101707 (May 15, 2012); http://dx.doi.org/10.1117/1.OE.51.10.101707

Online Publication Date: May 15, 2012

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An algorithm based on differential evolution (DE) with adaptive strategy selection for remote sensing image registration is designed. The paper has two major contributions. One contribution is the reduction of the computation time for a better result, i.e., fitness function approximate, which is based on multi-resolution processing and histogram matching. The second contribution is an adaptive strategy known as probability matching integration. The probability matching technique is employed in DE to autonomously select the most suitable strategy while solving the problem. To the best of our knowledge, the proposed method is the first adaptive strategy selection-based approach for image registration. In our experiments, the proposed method significantly outperforms previously proposed image registration method based on DE.
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