A visual model which gives a distortion measure for coding artifacts in images is presented. Given the original and the reproduced image as inputs, the model output is a numerical value, which quantifies the visibilit...
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A visual model which gives a distortion measure for coding artifacts in images is presented. Given the original and the reproduced image as inputs, the model output is a numerical value, which quantifies the visibility of error in a region of the reproduced image. The model aims to predict accurately the visibility of the common types of coding artifacts blocking, ringing and blurring. visual sensitivity to these artifacts is measured using psyche-visual experiments. The sensitivity measures thus obtained are used to derive the visual model which predicts the visibility of error. The final model is tested on real images, and the results show that the error visibility predicted by the model correlates well with the subjective ranking.< >
To design psychovisual quantizers, experiments based on the visibility of the quantization noise have been conducted by Saadane, Senane and Barba (see visualcommunications and imageprocessing, Oct. 1994). The result...
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To design psychovisual quantizers, experiments based on the visibility of the quantization noise have been conducted by Saadane, Senane and Barba (see visualcommunications and imageprocessing, Oct. 1994). The results obtained show that for a given visual decomposition scheme and within a subband, the decision thresholds and reconstruction levels follow a linear law with an interval quantization varying with frequency and orientation. In this paper, and in order to examine the masking effects on the perception of quantization noise, further experiments have been conducted by keeping the same methodology and the same decomposition scheme as Saadane et. al. Two important results have been obtained. First the masking didn't affect the linear behavior observed when no masking was considered. Secondly, with the contrast definition used, and even a slight increase in the quantization interval has been observed for the radial subbands, the masking was essentially due to the angular subbands.< >
This paper describes a method for coding arbitrarily shaped image segments. The method uses an iterative technique based on the theory of successive projection onto convex sets to determine the best transform coeffici...
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This paper describes a method for coding arbitrarily shaped image segments. The method uses an iterative technique based on the theory of successive projection onto convex sets to determine the best transform coefficients. It uses block transforms with frequency domain region-zeroing and space domain region-enforcing operations for effective coding of image segments of arbitrary shape. A major strength of this method is that it can be implemented in real-time using existing codec hardware at an insignificant additional cost.< >
We present a novel technique to encode video sequences, that performs a region-based decomposition of each frame on the basis of motion information. Using the segmentation map, any region in a frame to be encoded will...
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We present a novel technique to encode video sequences, that performs a region-based decomposition of each frame on the basis of motion information. Using the segmentation map, any region in a frame to be encoded will be predicted from a single reference frame, using motion compensated prediction. The use of a single reference frame avoids feedback of the prediction error information in the prediction of successive frames. Coding is simply obtained by describing the segmentation map and the associated motion information. Error information will not be provided for low bit-rate applications. The segmentation map is described using a quadtree structure. Within such a tree structure, we show how motion information can be predicted either spatially or temporally, so as to minimize redundancy of information. The motion and segmentation information are estimated on the basis of a two stage process using the frame to be encoded and the reference frame: (1) a hierarchical top-down decomposition; (2) a bottom-up merging strategy. The proposed posed method is used to encode to encode QCIF video sequences with a reasonable duality at a 10 frame/s rate using roughly 20 kbit/s.< >
Proposes a novel approach to segmentation using a combination of Hebbian learning and competitive learning in a self-organizing manner. The network is modular, with each module corresponding to a different class of th...
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Proposes a novel approach to segmentation using a combination of Hebbian learning and competitive learning in a self-organizing manner. The network is modular, with each module corresponding to a different class of the input data. A module consists of a weight vector that is calculated during an initial training period. The appropriate class for a given input vector is determined by a maximum entropy classifier. The resulting network consistently extracts perceptually relevant features from image data. As well, the class representations are analogous to the arrangement of directionally sensitive columns in the visual cortex.< >
The aim of image restoration is to find an estimate of the ideal image using a priori information about blur and/or noise and/or the ideal image. Classical criterion are minimum least square, minimum mean square error...
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The aim of image restoration is to find an estimate of the ideal image using a priori information about blur and/or noise and/or the ideal image. Classical criterion are minimum least square, minimum mean square error or maximum a posteriori probability. The choice of the criterion used to measure the estimation quality is crucial for the design of the restoration algorithm. The authors propose a new criterion based on a visual model: it is based on perceptual masking. Thereafter, they propose a new restoration algorithm dealing only with additive noise. The perceptual components of the image to restore which are corrupted by an additive noise above a visibility threshold are simply set to zero. Some results obtained for the post-processing of JPEG images are presented.< >
Proposes a pel adaptive image restoration algorithm for coded video signals, where ringing effects near sharp edges are smoothed out and blocking effects are removed without blurring edges at the decoder. The basic id...
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Proposes a pel adaptive image restoration algorithm for coded video signals, where ringing effects near sharp edges are smoothed out and blocking effects are removed without blurring edges at the decoder. The basic idea in this algorithm is that noise in block coded images is estimated from local statistics of image and quantization information and that each pixel data is estimated adaptively using linear least mean square error method. Since local mean and local variance for each pixel are the main calculation in the proposed algorithm, it is readily adaptable to real-time imageprocessing. The simulation examples of processed images coded by MPEG are presented to demonstrate that a significant improvement in subjective quality has been achieved.< >
We utilize speech information to improve the quality of audio/visualcommunications, such as videotelephony, videoconferencing, and multimedia. In particular, marriage of speech processing and imageprocessing can sol...
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We utilize speech information to improve the quality of audio/visualcommunications, such as videotelephony, videoconferencing, and multimedia. In particular, marriage of speech processing and imageprocessing can solve problems related to lip synchronization. Two main techniques proposed in this paper are: speech-assisted interpolation and speech-assisted coding of talking head video. Audio/video sequences are presented to demonstrate our techniques.< >
We present a technique for improving the applicability of complete, nonorthogonal, multiresolution transforms to image coding. As is well known, the L/sup 2/ norm of the quantization error is not preserved by nonortho...
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We present a technique for improving the applicability of complete, nonorthogonal, multiresolution transforms to image coding. As is well known, the L/sup 2/ norm of the quantization error is not preserved by nonorthogonal transforms, so the L/sup 2/ reconstruction error may be unacceptably large. However, given the quantizers and synthesis filters, we show that this artifact can be eliminated by formulating the coding problem as that of minimizing the L/sup 2/ reconstruction error over the set of possible encoded images. This high-dimensional, discrete optimization problem is solved using a multiscale relaxation algorithm. Bounds on the coding gain over the standard coding technique are derived. Experiments using biorthogonal spline filters demonstrate appreciable SNR gains over the standard coding technique, and comparable visual improvements.< >
In second generation image compression techniques the image to be compressed is first segmented. The pixels are divided into mutually exclusive spatial regions based on some criteria. After segmentation, the image con...
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In second generation image compression techniques the image to be compressed is first segmented. The pixels are divided into mutually exclusive spatial regions based on some criteria. After segmentation, the image consists of regions separated by contours. Then, the information is coded describing the shapes and interiors of the regions. The interiors of the regions are usually encoded using polynomials. The objective of this paper is to encode the interior of the regions by stochastic vector quantization techniques. If the segmentation process has been well defined and the obtained regions are homogeneous, then it is possible to design a specific codebook suited to the statistics of each region. The approach is to design the codebook according to some previously defined model for the regions of the image found in the segmentation process. If the approach is combined with efficient contour coding techniques, good visual results for high compression rates are obtained.< >
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