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Pentagraph image fusion scheme for motion blur prevention using multiple monochromatic images

APPLIED OPTICS 2016年第11期55卷 3096-3103页

作者： Volfman, Alon A. Mendlovic, David Raz, Ariel Tel Aviv Univ Fac Engn IL-69978 Tel Aviv Israel

This paper introduces the pentagraph image fusion (PIF) scheme for motion-related blur prevention in images. The PIF algorithm processes five monochromatic images into a single, low-noise, no-blur color image. The images are acquired using a new photography scheme, sequential filter photography (SFP), where instead of using a stationary Bayer pattern color filter array in front of the image sensor, a tunable color filter array is used. Using this approach, several monochromatic images are captured one by one and later fused into one color image. The SFP introduces various advantages such as higher resolution, better SNR, and the ability to control both exposure time and color filter separately for each image. The PIF algorithm harnesses all the advantages of SFP for the first time, to the best of our knowledge, in the field of blur-free image acquisition. Five images are taken with controllable exposure time and color filter, three images for the color bands, and two high-signal panchromatic images. These images are fused together to be a single, low-noise, no-blur color image. The algorithm presents a generic approach of dealing with both local and global motion blur and does not require any user intervention. (C) 2016 Optical Society of America

关键词： image processing Deconvolution image reconstruction techniques Imaging systems multiframe image processing Fusion

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Space debris detection in optical image sequences

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APPLIED OPTICS 2016年第28期55卷 7929-7940页

作者： Xi, Jiangbo Wen, Desheng Ersoy, Okan K. Yi, Hongwei Yao, Dalei Song, Zongxi Xi, Shaobo Chinese Acad Sci Xian Inst Opt & Precis Mech 17 Xinxi Rd Xian 710119 Peoples R China Univ Chinese Acad Sci 19A Yuquan Rd Beijing 100039 Peoples R China Purdue Univ Sch Elect & Comp Engn 465 Northwestem Ave W Lafayette IN 47907 USA Chinese Acad Sci Suzhou Inst Nanotech & Nanobion 398 Ruoshui Rd Suzhou 215123 Peoples R China

We present a high-accuracy, low false-alarmrate, and low computational-cost methodology for removing stars and noise and detecting space debris with low signal-to-noise ratio (SNR) in optical image sequences. First, time-index filtering and bright star intensity enhancement are implemented to remove stars and noise effectively. Then, a multistage quasi-hypothesis-testing method is proposed to detect the pieces of space debris with continuous and discontinuous trajectories. For this purpose, a time-index image is defined and generated. Experimental results show that the proposed method can detect space debris effectively without any false alarms. When the SNR is higher than or equal to 1.5, the detection probability can reach 100%, and when the SNR is as low as 1.3, 1.2, and 1, it can still achieve 99%, 97%, and 85% detection probabilities, respectively. Additionally, two large sets of image sequences are tested to show that the proposed method performs stably and effectively. (C) 2016 Optical Society of America

关键词： Detection Digital image processing image recognition algorithms and filters Pattern recognition target tracking multiframe image processing Telescopes

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Fast two-dimensional super-resolution image reconstruction algorithm for ultra-high emitter density

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OPTICS LETTERS 2015年第13期40卷 2989-2992页

作者： Huang, Jiaqing Gumpper, Kristyn Chi, Yuejie Sun, Mingzhai Ma, Jianjie Ohio State Univ Davis Heart & Lung Res Inst Dept Surg Columbus OH 43210 USA Ohio State Univ Dept Elect & Comp Engn Columbus OH 43210 USA Ohio State Univ Dept Biomed Informat Columbus OH 43210 USA

Single-molecule localization microscopy achieves sub-diffraction-limit resolution by localizing a sparse subset of stochastically activated emitters in each frame. Its temporal resolution is limited by the maximal emitter density that can be handled by the image reconstruction algorithms. Multiple algorithms have been developed to accurately locate the emitters even when they have significant overlaps. Currently, compressive-sensing-based algorithm (CSSTORM) achieves the highest emitter density. However, CSSTORM is extremely computationally expensive, which limits its practical application. Here, we develop a new algorithm (MempSTORM) based on two-dimensional spectrum analysis. With the same localization accuracy and recall rate, MempSTORM is 100 times faster than CSSTORM with l(1)-homotopy. In addition, MempSTORM can be implemented on a GPU for parallelism, which can further increase its computational speed and make it possible for online super-resolution reconstruction of high-density emitters. (C) 2015 Optical Society of America

关键词： image processing Superresolution multiframe image processing Microscopy

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Simultaneous digital super-resolution and nonuniformity correction for infrared imaging systems

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APPLIED OPTICS 2015年第21期54卷 6508-6515页

作者： Meza, Pablo Machuca, Guillermo Torres, Sergio Martin, Cesar San Vera, Esteban Univ La Frontera Dept Ingn Elect Temuco Chile Univ Concepcion Dept Ingn Elect Concepcion Chile Univ Concepcion Ctr Opt & Photon Concepcion Chile Duke Univ Dept Elect & Comp Engn Durham NC 27706 USA

In this article, we present a novel algorithm to achieve simultaneous digital super-resolution and nonuniformity correction from a sequence of infrared images. We propose to use spatial regularization terms that exploit nonlocal means and the absence of spatial correlation between the scene and the nonuniformity noise sources. We derive an iterative optimization algorithm based on a gradient descent minimization strategy. Results from infrared image sequences corrupted with simulated and real fixed-pattern noise show a competitive performance compared with state-of-the-art methods. A qualitative analysis on the experimental results obtained with images from a variety of infrared cameras indicates that the proposed method provides super-resolution images with significantly less fixed-pattern noise. (C) 2015 Optical Society of America

关键词： Superresolution Infrared imaging Noise in imaging systems multiframe image processing

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Robust multi-object tracking using deep learning framework

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JOURNAL OF OPTICAL TECHNOLOGY 2015年第8期82卷 516-527页

作者： Pang, Sh Ch Du, Anan Yu, Zh. Zh. China Jilin Univ Coll Comp Sci & Technol Changchun Peoples R China

Object appearance representation is crucial to any visual tracker. In order to improve the appearance representation, we propose a deep compact and high-level appearance representation applied to a multi-object tracking algorithm, which is called Deep Multi-object Tracking. In this paper, we adopt the deep learning framework to offline obtain generic image features with auxiliary natural images and online fine-tune our Deep Multi-object Tracking system to adapt to appearance changes of the moving objects. Besides, we have fully considered the temporal information denoting the dynamic duration time of each object. Based on the temporal information and particle filter, our Deep Multi-object Tracking algorithm can effectively generate an online learning and updating model to form a discriminative appearance scheme to achieve successful multi-object tracking. Experiments show that the proposed Deep Multi-object Tracking performs well both indoor and outdoor, where the objects undergo large pose, scale, occlusion, and illumination variations in complex scenes including abnormal ones. (C) 2015 Optical Society of America.

关键词： image analysis Machine vision multiframe image processing Neural networks Pattern recognition Vision processor architecture

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Large aperture focus stacking with max-gradient flow by anchored rolling filtering

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APPLIED OPTICS 2016年第20期55卷 5304-5309页

作者： Yin, Xuanwu Wang, Guijin Li, Wentao Liao, Qingmin Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China Tsinghua Univ Dept Elect Engn Grad Sch Shenzhen Shenzhen 518055 Peoples R China

Focus stacking is a computational technique to extend the depth of field through combining multiple images taken at various focus distances. However, in the large aperture case, there are always defects caused by the large blur scale, which, to the best of our knowledge, has not been well studied. In our work, we propose a max-gradient flow-based method to reduce artifacts and obtain a high-quality all-in-focus image by anchored rolling filtering. First, we define a max-gradient flow to describe the gradient propagation in the stack. The points are divided into trivial and source points with this flow. The source points are extracted as true edge points and are utilized as anchors to refine the depth map and the composited all-in-focus image iteratively. The experiments show that our method can effectively suppress the incorrect depth estimations and give a high-quality all-in-focus image. (C) 2016 Optical Society of America

关键词： image reconstruction-restoration multiframe image processing image reconstruction techniques

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Change detection in underwater imagery

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JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS image SCIENCE AND VISION 2016年第3期33卷 301-313页

作者： Seemakurthy, Karthik Rajagopalan, A. N. Indian Inst Technol Dept Elect Engn Image Proc & Comp Vis Lab Chennai 600036 Tamil Nadu India

In this work, we deal with the problem of change detection in an underwater scenario given an unblurred-blurred image pair of a planar scene taken at different times. The blur is primarily due to the dynamic nature of the water surface and its nature is space-invariant in the presence of cyclic water flows. Exploiting the sparsity of the induced blur as well as the occlusions, we propose a distort-difference pipeline that employs an alternating minimization framework to perform change detection in the presence of geometric distortions (skew) as well as photometric degradations (blur and global illumination variations). The method can effectively yield both sharp and blurred occluder maps. Using synthetic as well as real data, we demonstrate how the proposed technique advances the state of the art. (C) 2016 Optical Society of America

关键词： Water Matrix methods in paraxial optics Imaging through turbulent media multiframe image processing Refraction

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DMD-based implementation of patterned optical filter arrays for compressive spectral imaging

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JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS image SCIENCE AND VISION 2015年第1期32卷 80-89页

作者： Rueda, Hoover Arguello, Henry Arce, Gonzalo R. Univ Delaware Dept Elect & Comp Engn Newark DE 19716 USA Univ Ind Santander Dept Comp Engn Santander 680002 Colombia

Compressive spectral imaging (CSI) captures multispectral imagery using fewer measurements than those required by traditional Shannon-Nyquist theory-based sensing procedures. CSI systems acquire coded and dispersed random projections of the scene rather than direct measurements of the voxels. To date, the coding procedure in CSI has been realized through the use of block-unblock coded apertures (CAs), commonly implemented as chrome-on-quartz photomasks. These apertures block or permit us to pass the entire spectrum from the scene at given spatial locations, thus modulating the spatial characteristics of the scene. This paper extends the framework of CSI by replacing the traditional block-unblock photomasks by patterned optical filter arrays, referred to as colored coded apertures (CCAs). These, in turn, allow the source to be modulated not only spatially but spectrally as well, entailing more powerful coding strategies. The proposed CCAs are synthesized through linear combinations of low-pass, high-pass, and bandpass filters, paired with binary pattern ensembles realized by a digital micromirror device. The optical forward model of the proposed CSI architecture is presented along with a proof-of-concept implementation, which achieves noticeable improvements in the quality of the reconstruction. (C) 2014 Optical Society of America

关键词： Imaging systems Coded aperture imaging multiframe image processing Multispectral and hyperspectral imaging Wavelength filtering devices

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All-optical coaxial framing photography using parallel coherence shutters

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OPTICS LETTERS 2017年第3期42卷 415-418页

作者： Chen Guanghua Li Jianfeng Peng Qixian Liu Shouxian Liu Jun China Acad Engn Phys Inst Fluid Phys Mianyang 621900 Sichuan Peoples R China

An all-optical framing camera has been developed to obtain serial images of high temporal and spatial resolution with identical spatial benchmark, identical temporal benchmark, and identical chromatic benchmark in a single shot. A train of laser probe pulses with identical wavelength coaxially illuminate the target and form sequentially timed images by means of parallel coherence shutters. A coherence shutter only selects one of the probe pulses to form a nonmultiplexing hologram. The other probe pulses superpose incoherently on the hologram as the background. By this method, each hologram is entirely separated from the others both in spatial and temporal domains. Two kinds of ultrafast physical process experiments, including laser driving air and laser driving aluminum foil, were performed to verify the feasibility of the parallel coherence shutters. (C) 2017 Optical Society of America

关键词： Digital holography multiframe image processing Coherence imaging

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COLOR AND LUMINANCE CORRECTIONS FOR PANORAMIC image STITCHING

COMPUTER OPTICS

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COMPUTER OPTICS 2018年第5期42卷 885-897页

作者： Kanaeva, I. A. Bolotova, Yu. A. Tomsk Polytech Univ Tomsk Russia Tomsk Polytech Univ Informat Technol Tomsk Russia

The article gives a detailed analysis of seamless image stitching methods into a panorama from an overlapping image set. Source images usually have varying colors and luminance due to cameras' position changing. Various approaches of blending and color correction algorithms for source images are presented. This paper illustrates the optimal technic for parallel evaluation of color correction coefficients in all overlapping areas. High quality of our blending method is confirmed by color and structure similarities based on PSNR and SSIM indexes accordingly.

关键词： multiframe image processing color blending image analysis panoramic image stitching

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