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A test method for dynamic imaging of space TDICCD (Time Delay and Integration Charge Coupled Devices) camera was presented in this paper. The test method adopted the PLL (Phase Locked Loop) technology and CMAC (Cerebella Model Articulation Controller) friction compensation as control strategy. Furthermore, According to this method, a test system for dynamic imaging of space TDICCD camera was designed...
Normalized cross-correlation (NCC) is a common matching technique to tolerate radiometric differences between stereo images. However, traditional rectangle-based NCC tends to blur the depth discontinuities. This paper proposes an efficient stereo algorithm with NCC over shape-adaptive matching regions, producing depth-discontinuity preserving disparity maps while remaining the advantage of robustness...
This paper proposes a real-time design for accurate stereo matching on Compute Unified Device Architecture (CUDA). We adopt a leading local algorithm for its high data parallelism. A GPU-oriented bitwise fast voting method is proposed to effectively improve the matching accuracy, which is enormously faster than the histogram-based approach. The whole algorithm is parallelized on CUDA at a fine granularity,...
In this paper, we propose an efficient local stereo algorithm for accurate disparity estimation. First, we attain initial disparity estimates by iterating a cross-based cost aggregation process. Then, we propose a robust voting scheme to refine the initial estimates based on a piecewise smoothness prior, improving the quality in occluded regions and low-textured regions effectively. The refinement...
Partial occlusion is a difficult problem in computer vision since whether the object is changed or occluded is ambiguous, especially when distinguishing it only from the object boundary. In this paper, we proposed a novel idea to solve this problem by taking shape matching as a morphing processing. A mass-spring model is constructed from the point set which is sampled from a template (or reference)...
We propose an area-based local stereo matching algorithm that yields accurate disparity estimates, while achieving the real-time speed completely on the graphics processing unit (GPU). For a local stereo method, the key challenge is to decide an appropriate support window for the pixel under consideration. Our stereo method starts with computing an upright local cross adaptively for each anchor pixel,...
We propose an area-based local stereo matching algorithm for accurate disparity estimation across all image regions. A well-known challenge to local stereo methods is to decide an appropriate support window for the pixel under consideration, adapting the window shape or the pixelwise support weight to the underlying scene structures. Our stereo method tackles this problem with two key contributions...
We present a scalable stereo matching algorithm based on a Locally Adaptive Polygon Approximation (LAPA) technique. For accurate local stereo matching, pixel-wise adaptive polygon-based support windows are constructed to approximate spatially varying image structures. Central to building these pixel-wise polygons is a fast algorithm that adaptively decides a set of directional scales, utilizing intensity...
The scale and rotation change of target make the effect of image matching recognition worse. In order to resolve this problem, a novel recognition algorithm based on intersecting cortical model (ICM) icon was introduced, which provides an invariant representation of the object's rotation, scaling and translation. First, the real-time map and the reference map were input to ICM model to get icons....
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