It is well known that wavelets provide good non-linear approximation of one-dimensional (1-D) piecewise smooth functions. However, it has been shown that the use of a basis with good approximation properties does not ...
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It is well known that wavelets provide good non-linear approximation of one-dimensional (1-D) piecewise smooth functions. However, it has been shown that the use of a basis with good approximation properties does not necessarily lead to a good compression algorithm. The situation in 2-D is much more complicated since wavelets are not good for modeling piecewise smooth signals (where discontinuities are along smooth curves). The purpose of this work is to analyze the performance of compression algorithms for 2-D piecewise smooth functions directly in a rate distortion context. We consider some simple image models and compute rate distortion bounds achievable using oracle based methods. We then present a practical compression algorithm based on optimal quadtree decomposition that, in some cases, achieve the oracle performance.
In this work, a neural controller for delay compensation in image samples detected by an active vision system of robotic heads, in ocular tracking tasks is presented. This control architecture based on CMAC (cerebella...
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In this work, a neural controller for delay compensation in image samples detected by an active vision system of robotic heads, in ocular tracking tasks is presented. This control architecture based on CMAC (cerebellar model articulation controller) model has the capacity of learning favored trajectories with less prediction error. This property is very important in robotic tasks of controlling the grasping or assembling of objects by a robotic arm. The main advantage of this cerebellar model is that the output is evaluated by means of a small number of memory cells that implies a high answer speed. Indeed, this visual robotic control avoids (as does the human system) the need to know the kinematics of the process. This prediction module has been integrated in an architecture of visual-motor coordination based on VAM (vector associative maps) models.
Change detection using a difference picture has been used to detect the location of moving targets and to track them. This method needs the assumption of a static camera, and global motion compensation is required in ...
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Change detection using a difference picture has been used to detect the location of moving targets and to track them. This method needs the assumption of a static camera, and global motion compensation is required in the case of a moving camera. We suggest a method for finding minimum bounding rectangles (MBRs) of moving targets in the image sequences using moving region detection, especially with a moving camera. If the global motion parameter is inaccurately estimated, the estimated locations of targets will not be accurate either. To alleviate this problem, we introduce the concept of the confidence measure and achieve more accurate estimation of global motion. With a moving camera, the new global motion estimation algorithm performs more precisely and it reduces the background compensation errors for change detection. Experimental results show that the proposed method successfully removes the background region and extracts MBRs of the targets.
We study the Laplacian pyramid (LP) as a frame operator, and this reveals that the usual reconstruction is suboptimal. With orthogonal filters, the LP is shown to be a tight frame, thus the optimal linear reconstructi...
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We study the Laplacian pyramid (LP) as a frame operator, and this reveals that the usual reconstruction is suboptimal. With orthogonal filters, the LP is shown to be a tight frame, thus the optimal linear reconstruction using the dual frame operator has a simple structure as symmetrical with the forward transform. For more general cases, we propose an efficient filter bank for reconstruction in the LP that is shown to perform better than the usual method. Numerical results indicate that gains of more than 1 dB are actually achieved.
In this paper we assess the independence of the optimization of source and channel coding parameters. We propose a method to separate the source and channel coding optimization as much as possible while maintaining th...
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ISBN:
(纸本)0819437034
In this paper we assess the independence of the optimization of source and channel coding parameters. We propose a method to separate the source and channel coding optimization as much as possible while maintaining the possibility of joint optimization. We theoretically derive key parameters that must be passed through an interface between source and channel coding. This separation greatly reduces the complexity of the optimization problem and enhances the flexibility.
This paper introduces a new compression method for palettized images, which supports progressive refinement of the color information in contrast to the resolution refinement used in standard methods like interlaced GI...
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ISBN:
(纸本)0819437034
This paper introduces a new compression method for palettized images, which supports progressive refinement of the color information in contrast to the resolution refinement used in standard methods like interlaced GIF. Such, fine image details can be recognized after decoding only a small part of the compressed image data. Achieved compression ratios are comparable to those of interlaced GIF or PKG. The method combines color map sorting with bitplane by bitplane prediction and Golomb coding of the pixel held.
Low bit rate image coding is essential for many visual communication applications. However, it yields visually annoying artifacts that highly degrade the perceptual quality of image data. In this paper we propose a no...
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ISBN:
(纸本)0819437034
Low bit rate image coding is essential for many visual communication applications. However, it yields visually annoying artifacts that highly degrade the perceptual quality of image data. In this paper we propose a novel method for reducing the blocking artifact that occurs when using DCT image coding at low bit rates. The blocking artifact has varied visibility in different region, that is, it is more visible in a smooth region than detailed region such as textures and edges. Hence, the proposed method is based on image segmentation and then thresholding the coefficients of different regions with adaptive thresholds. The proposed method gives consistent improvement over the previous methods for deblocking in term of peak signal-to-noise ratio (PSNR), edge variance (EV), and visual quality.
This paper proposes a novel algorithm to accelerate the encoding procedure of fractal image compression. We develop an indexing technology to access candidate domain blocks. The location of maximal gradient is adopted...
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ISBN:
(纸本)0819437034
This paper proposes a novel algorithm to accelerate the encoding procedure of fractal image compression. We develop an indexing technology to access candidate domain blocks. The location of maximal gradient is adopted as the key for indexing. Only those blocks whose positions of maximal gradients matching that of a given range block are tested. In our experiments, the new algorithm promises good performance. It takes few seconds to encode a 512 by 512 image on a Pentium Il 450 PC with a slight loss of decoded image fidelity.
In this paper, we introduce an unequal error protection technique for foveation-based error resilience over highly error-prone mobile networks. For point-to-point visualcommunications, visual quality can be significa...
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ISBN:
(纸本)0780362985
In this paper, we introduce an unequal error protection technique for foveation-based error resilience over highly error-prone mobile networks. For point-to-point visualcommunications, visual quality can be significantly increased by using foveation-based error resilience where each frame is divided into foveated and background layers according to the gaze direction of the human eye, and two bitstreams are generated. In an effort to increase the source throughput of foveated layer, we employ unequal delay-constrained ARQ and RCPC (rate compatible punctured convolutional) codes in H.223 Annex C. In the simulation, the visual quality is increased in the range of 0.3 dB to 1 dB over channel SNR 5 dB to 15 dB.
In this paper, the problem of DCT information recovery in the transmission of coded visual data over packet networks is addressed. The loss of a packet conveying coded block data leads to the unsuccessful reconstructi...
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In this paper, the problem of DCT information recovery in the transmission of coded visual data over packet networks is addressed. The loss of a packet conveying coded block data leads to the unsuccessful reconstruction of the relevant area, with consequent degradation of the received image quality. The proposed method allows recovery of a subset of the missing DCT coefficients sufficient to achieve good reconstruction quality of the lost block, based on the available surrounding information. To this purpose, a neural predictor was carefully designed and suitably trained with an appropriate set of synthetic and natural patterns. An extensive testing phase, performed on a large set of images with different frequency characteristics, revealed that the method provides very good reconstruction capabilities.
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