image-based rendering is a method to synthesise novel views from a set of given real images. Two methods to extrapolate novel views of complex scenes with occlusions and large depth discontinuities from images of a mo...
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image-based rendering is a method to synthesise novel views from a set of given real images. Two methods to extrapolate novel views of complex scenes with occlusions and large depth discontinuities from images of a moving uncalibrated multi-camera rig are discribed. The real camera viewpoints are calibrated from the image data and dense depth maps are estimated for each real view. Novel views are synthesised from this representation with view-dependent image-based rendering techniques at interactive rates. Since the 3-D scene geometry is available in this approach, it is well suited for mixed reality applications where synthetic 3-D objects are seamlessly embedded in the novel view.
The Data- Intensive Architecture ( DIVA) system employs processing- In- Memory ( PIM) chips as smart-memory coprocessors. This architecture exploits inherent memory bandwidth both on chip and across the system to targ...
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The Data- Intensive Architecture ( DIVA) system employs processing- In- Memory ( PIM) chips as smart-memory coprocessors. This architecture exploits inherent memory bandwidth both on chip and across the system to target several classes of bandwidth- limited applications, including multimedia applications and pointer- based and sparse- matrix computations. The DIVA project has built a prototype development system using PIM chips in place of standard DRAMs to demonstrate these concepts. We have recently ported several demonstration kernels to this platform and have exhibited a speedup of 35x on a matrix transpose operation. This paper focuses on the 32- bit scalar and 256- bit WideWord integer processing components of the first DIVA prototype PIM chip, which was fabricated in TSMC 0.18 mum technology. In conjunction with other publications, this paper demonstrates that impressive gains can be achieved with very little " smart" logic added to memory devices. A second PIM prototype that includes WideWord floating- point capability is scheduled to tape out in August 2003.
imageprocessing techniques are very important in archaeological data evaluation Espericially data, closer to the surface are carrying to important knowledge and desired to be defected. We assume to process the raw da...
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One of the main problems in visual signalprocessing is incomplete information owing an occlusion of objects by other objects. It is well known that correlation filters mainly use contour information of objects to car...
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One of the main problems in visual signalprocessing is incomplete information owing an occlusion of objects by other objects. It is well known that correlation filters mainly use contour information of objects to carry out pattern recognition. However, in real applications object contours are often disappeared. In these cases conventional correlation filters without training yield a poor performance. In this paper two novel methods based on correlation filters with training for recognition of partially occluded objects are proposed. The methods improve significantly discrimination capability of conventional correlation filters. The first method performs training of a correlation filter with both a target and objects to be rejected. In the second proposal two different correlation filters are designed. They deal independently with contour and texture information to improve recognition of partially occluded objects. Computer simulation results for various test images are provided and discussed.
Multimedia applications such as video and imageprocessing are often characterized by a large number of data accesses (i.e. RAM accesses). In many digital signal-processingapplications, the array access patterns are ...
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ISBN:
(纸本)0819458325
Multimedia applications such as video and imageprocessing are often characterized by a large number of data accesses (i.e. RAM accesses). In many digital signal-processingapplications, the array access patterns are regular and periodic. In these cases, optimized Pipelined Memory Access Controllers can be generated. This technique is used to improve the pipeline access mode to RAM by creating specialized hardware components for generating addresses and packing and unpacking data items. In this paper we focus on the design, implementation and validation of memory interfacing modules that can be automatically generated from a behavioural synthesis tool and which can efficiently handle predictable address patterns as well as unpredictable ones (dynamic address computations) in a pipeline way. We also analyze the benefits of balancing dynamic address computations from datapath to specialized computation units placed in the memory controller, optimizing bitwise of operators and data locality i.e. reducing the power consumption.
Magnetic resonance (MR) images acquired with a high temporal resolution or high spatial resolution are usually with a penalty of low signal to noise ratio (SNR). It is necessary to remove the noise artifacts with impo...
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ISBN:
(纸本)0819457213
Magnetic resonance (MR) images acquired with a high temporal resolution or high spatial resolution are usually with a penalty of low signal to noise ratio (SNR). It is necessary to remove the noise artifacts with important image features such as edges preserved. hi this paper, we propose to use the improved wavelet-based multiscale anisotropic diffusion algorithm for MR imaging. Experimental results demonstrate that this denoising algorithm can significantly improve the SNR for MR images while preserving edges with good visual quality. The denoising results indicate that in MR imaging applications, we can almost doubly improve the temporal resolution or improve the spatial resolution while achieving high SNR and acceptable image quality.
Local illumination changes due to shadows often reduce the quality of object-based video composition and mislead object recognition. This problem makes shadow detection a desirable tool for a wide range of application...
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Local illumination changes due to shadows often reduce the quality of object-based video composition and mislead object recognition. This problem makes shadow detection a desirable tool for a wide range of applications, such as video production and visual surveillance. In this paper, an algorithm for the isolation of video objects from the local illumination changes they generate in real world sequences when camera, illumination and the scene characteristics are not known is presented. The algorithm combines a change detector and a shadow detector with a spatio-temporal verification stage. Colour information and spatio-temporal constraints are embedded to define the overall algorithm. Colour information is exploited in a selective way. First, relevant areas to analyse are identified in each image. Then, the colour components that carry most of the needed information are selected. Finally, spatial and temporal constraints are used to verify the results of the colour analysis. The proposed algorithm is demonstrated on both indoor and outdoor video sequences. Moreover, performance comparisons show that the proposed algorithm outperforms state-of-the-art methods.
作者：
Yu, xYSun, HWuhan Univ
Sch Elect Informat Signal Proc Lab Wuhan 430072 Peoples R China
A coarse-to-fine automatic point-based image registration method is proposed in this paper. At the first stage, clustering is used to determine the scale parameter and the rotational parameter candidates between image...
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ISBN:
(纸本)354027894X
A coarse-to-fine automatic point-based image registration method is proposed in this paper. At the first stage, clustering is used to determine the scale parameter and the rotational parameter candidates between images. Convex hull vertices correlation is applied subsequently to determine the correct rotational parameter. With the coordinates of matched point pairs and the above parameters, the translational parameter and the coarse registration result can be determined. At the second stage, control point pairs, which determine parameters of mapping polynomial, are formed by iterative convex hull vertices matching. Thus the registration result is refined. Experiments indicate that this approach can automatically align images in different resolutions.
In wavelets based coding applications, resolution scalability is achieved by retaining the low pass signal subband corresponds to the required resolution and discarding other high pass wavelet subbands. Aliasing is a ...
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In wavelets based coding applications, resolution scalability is achieved by retaining the low pass signal subband corresponds to the required resolution and discarding other high pass wavelet subbands. Aliasing is a common problem present in such downsampling. In this paper a novel technique for improving the low pass filter for improved downsampling is presented. This method uses an extra update step followed by P+U lifting scheme. The preprocessing update step is chosen as the dual update step associated with the wavelet. The spatially adaptive low pass (SALP) filtering concept is used for the second update step, leading to an overall low pass filter whose size adapts to the underlying signal content. The filter choices for the second update step is recovered at the decoder without any bookkeeping. Results using the 2D 5/3 wavelet with the extra pre-processing update step show improvements over conventional wavelets.
The effect of assuming and using non-Gaussian attributes of underlying source signals for separating/encoding patterns is investigated, for application to terrain categorization (TERCAT) problems. Our analysis provide...
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The effect of assuming and using non-Gaussian attributes of underlying source signals for separating/encoding patterns is investigated, for application to terrain categorization (TERCAT) problems. Our analysis provides transformed data, denoted as "Independent Components," which can be used and interpreted in different ways. The basis vectors of the resulting transformed data are statistically independent and tend to align themselves with source signals. In this effort, we investigate the basic formulation designed to transform signals for subsequent processing or analysis, as well as a more sophisticated model designed specifically for unsupervised classification. Mixes of single band images are used, as well as simulated color infrared and Landsat. A number of experiments are performed. We first validate the basic formulation using a straightforward application of the method to unmixsignal data in image space. We next show the advantage of using this transformed data compared to the original data for visually detecting TERCAT targets of interest. Subsequently, we test two methods of performing unsupervised classification on a scene that contain a diverse range of terrain features, showing the benefit of these methods against a control method for TERCAT applications.
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