670 research outputs found

    Radix-2n serial–serial multipliers

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    All serial–serial multiplication structures previously reported in the literature have been confined to bit serial–serial multipliers. An architecture for digit serial–serial multipliers is presented. A set of designs are derived from the radix-2n design procedure, which was first reported by the authors for the design of bit level pipelined digit serial–parallel structures. One significant aspect of the new designs is that they can be pipelined to the bit level and give the designer the flexibility to obtain the best trade-off between throughput rate and hardware cost by varying the digit size and the number of pipelining levels. Also, an area-efficient digit serial–serial multiplier is proposed which provides a 50% reduction in hardware without degrading the speed performance. This is achieved by exploiting the fact that some cells are idle for most of the multiplication operation. In the new design, the computations of these cells are remapped to other cells, which make them redundant. The new designs have been implemented on the S40BG256 device from the SPARTAN family to prove functionality and assess performance

    Pre-processing of integral images for 3-D displays

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    This paper seeks to explore a method to accurately correct geometric distortions caused during the capture of three dimensional (3-D) integral images. Such distortions are rotational and scaling errors which, if not corrected, will cause banding and moire effects on the replayed image. The method for calculating the angle of deviation in the 3-D Integral Images is based on Hough Transform. It allows detection of the angle necessary for correction of the rotational error. Experiments have been conducted on a number of 3-D integral image samples and it has been found that the proposed method produces results with accuracy of 0.05 deg

    The refocusing distance of a standard plenoptic photograph

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    IEEE International Conference PaperIn the past years, the plenoptic camera aroused an increasing interest in the field of computer vision. Its capability of capturing three-dimensional image data is achieved by an array of micro lenses placed in front of a traditional image sensor. The acquired light field data allows for the reconstruction of photographs focused at different depths. Given the plenoptic camera parameters, the metric distance of refocused objects may be retrieved with the aid of geometric ray tracing. Until now there was a lack of experimental results using real image data to prove this conceptual solution. With this paper, the very first experimental work is presented on the basis of a new ray tracing model approach, which considers more accurate micro image centre positions. To evaluate the developed method, the blur metric of objects in a refocused image stack is measured and compared with proposed predictions. The results suggest quite an accurate approximation for distant objects and deviations for objects closer to the camera device

    A joint motion & disparity motion estimation technique for 3D integral video compression using evolutionary strategy

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    3D imaging techniques have the potential to establish a future mass-market in the fields of entertainment and communications. Integral imaging, which can capture true 3D color images with only one camera, has been seen as the right technology to offer stress-free viewing to audiences of more than one person. Just like any digital video, 3D video sequences must also be compressed in order to make it suitable for consumer domain applications. However, ordinary compression techniques found in state-of-the-art video coding standards such as H.264, MPEG-4 and MPEG-2 are not capable of producing enough compression while preserving the 3D clues. Fortunately, a huge amount of redundancies can be found in an integral video sequence in terms of motion and disparity. This paper discusses a novel approach to use both motion and disparity information to compress 3D integral video sequences. We propose to decompose the integral video sequence down to viewpoint video sequences and jointly exploit motion and disparity redundancies to maximize the compression. We further propose an optimization technique based on evolutionary strategies to minimize the computational complexity of the joint motion disparity estimation. Experimental results demonstrate that Joint Motion and Disparity Estimation can achieve over 1 dB objective quality gain over normal motion estimation. Once combined with Evolutionary strategy, this can achieve up to 94% computational cost saving

    Bit-level pipelined digit-serial array processors

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    A new architecture for high performance digit-serial vector inner product (VIP) which can be pipelined to the bit-level is introduced. The design of the digit-serial vector inner product is based on a new systematic design methodology using radix-2n arithmetic. The proposed architecture allows a high level of bit-level pipelining to increase the throughput rate with minimum initial delay and minimum area. This will give designers greater flexibility in finding the best tradeoff between hardware cost and throughput rate. It is shown that sub-digit pipelined digit-serial structure can achieve a higher throughput rate with much less area consumption than an equivalent bit-parallel structure. A twin-pipe architecture to double the throughput rate of digit-serial multipliers and consequently that of the digit-serial vector inner product is also presented. The effect of the number of pipelining levels and the twin-pipe architecture on the throughput rate and hardware cost are discussed. A two's complement digit-serial architecture which can operate on both negative and positive numbers is also presented

    Formes de contact ayant le mĂȘme champ de Reeb

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    2000 Mathematics Subject Classification: 37J55, 53D10, 53D17, 53D35.In this paper, we study contact forms on a 3-manifold having a common Reeb vector field R. The main result is that when the contact forms induce the same orientation, they are diffeomorphic

    Motion and disparity estimation with self adapted evolutionary strategy in 3D video coding

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    Real world information, obtained by humans is three dimensional (3-D). In experimental user-trials, subjective assessments have clearly demonstrated the increased impact of 3-D pictures compared to conventional flat-picture techniques. It is reasonable, therefore, that we humans want an imaging system that produces pictures that are as natural and real as things we see and experience every day. Three-dimensional imaging and hence, 3-D television (3DTV) are very promising approaches expected to satisfy these desires. Integral imaging, which can capture true 3D color images with only one camera, has been seen as the right technology to offer stress-free viewing to audiences of more than one person. In this paper, we propose a novel approach to use Evolutionary Strategy (ES) for joint motion and disparity estimation to compress 3D integral video sequences. We propose to decompose the integral video sequence down to viewpoint video sequences and jointly exploit motion and disparity redundancies to maximize the compression using a self adapted ES. A half pixel refinement algorithm is then applied by interpolating macro blocks in the previous frame to further improve the video quality. Experimental results demonstrate that the proposed adaptable ES with Half Pixel Joint Motion and Disparity Estimation can up to 1.5 dB objective quality gain without any additional computational cost over our previous algorithm.1Furthermore, the proposed technique get similar objective quality compared to the full search algorithm by reducing the computational cost up to 90%

    Depth mapping of integral images through viewpoint image extraction with a hybrid disparity analysis algorithm

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    Integral imaging is a technique capable of displaying 3–D images with continuous parallax in full natural color. It is one of the most promising methods for producing smooth 3–D images. Extracting depth information from integral image has various applications ranging from remote inspection, robotic vision, medical imaging, virtual reality, to content-based image coding and manipulation for integral imaging based 3–D TV. This paper presents a method of generating a depth map from unidirectional integral images through viewpoint image extraction and using a hybrid disparity analysis algorithm combining multi-baseline, neighbourhood constraint and relaxation strategies. It is shown that a depth map having few areas of uncertainty can be obtained from both computer and photographically generated integral images using this approach. The acceptable depth maps can be achieved from photographic captured integral images containing complicated object scene
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