Two fundamental motivations exist for designing remote sensing systems that are undersampled: (1) SNR considerations that motivate larger detectors to collect more photoevents per frame time and (2) the desire to maxi...
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Two fundamental motivations exist for designing remote sensing systems that are undersampled: (1) SNR considerations that motivate larger detectors to collect more photoevents per frame time and (2) the desire to maximize the field of view with a finite number of detectors. As a result, many remote sensing systems do not satisfy the Ny-quist sampling criterion, leading to measured images corrupted with a defect called aliasing. We describe a localized subpixel motion sensing algorithm that is used to properly place small blocks of the sequence of images in an upsampled space. Localized motion sensing enables dealiasing to be performed on image sequences with more complicated relative motion than simple translation. The presented results show improvements in both the edge response and subjective image quality. (C) 2002 Society of Photo-Optical Instrumentation Engineers.
An advanced center biased search algorithm for block motion estimation is proposed in this letter. It adopts an innovative center biased search strategy to get correct motion vector. The computational complexity is re...
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An advanced center biased search algorithm for block motion estimation is proposed in this letter. It adopts an innovative center biased search strategy to get correct motion vector. The computational complexity is reduced by strict application of the unimodal error surface assumption and half stop technique. Experimental results show that proposed algorithm has improved performance as compared to the conventional block matching algorithms.
Atmospheric turbulence adversely affects imaging systems by causing a random distribution of the index of refraction of the air through which the light must propagate. The resulting image degradation can seriously und...
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ISBN:
(纸本)0819437700
Atmospheric turbulence adversely affects imaging systems by causing a random distribution of the index of refraction of the air through which the light must propagate. The resulting image degradation can seriously undermine the effectiveness of the sensor. In many astronomical systems, which typically have a very narrow field of view, the entire image can be modeled by the convolution of the object with a single point spread function (PSF), and as a result of the narrow field of view, adaptive optical systems can be highly effective in correcting astronomical images. In the case of tactical infrared sensors the field of view is generally much larger than the isoplanatic angle, and the image cannot be modeled by a single point spread function convolved with the scene. Hence, adaptive optical solutions to wide angle infrared imaging over horizonatal paths would be difficult, if not impossible, and post-detection processing of the images is required to mitigate turbulence effects. The overall effect of turbulence within a given isoplanatic patch is not as strong as in the astronomical imaging case due to shorter paths and longer wavelengths. Tilt and low order turbulence modes dominate the aberration experienced within individual isoplanatic patches, greatly simplifying image reconstruction problems. In this paper Ne describe an algorithm for processing video sequences capable of partially correcting these turbulence effects. The algorithm is based on block matching algorithms used in video compression. Simulation results show that this algorithm reduces the squared error of the imagery, and subjectively better images are obtained.
In this paper, we investigate hardware implementation of block matching algorithms (BMA's) for motion estimation of moving sequences. Using systolic arrays, we propose VLSI architectures for the two-stage BMA and ...
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In this paper, we investigate hardware implementation of block matching algorithms (BMA's) for motion estimation of moving sequences. Using systolic arrays, we propose VLSI architectures for the two-stage BMA and full search (FS) BMA. The two-stage BMA using integral projections reduces greatly. computational complexity with its performance comparable td that of the FS BMA. The proposed hardware architectures for the two-stage BMA and FS BMA are faster than the conventional hardware architectures with lower hardware complexity. Also, the proposed architecture of the first stage of the two-stage BMA is modeled in VHDL and simulated. Simulation results show the functional validity of the proposed architecture.
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