A modified version of the Bezier-Bernstein polynomial approximation technique has been developed which gives local control of data points depending on an absolute error criterion. Based on this concept, two algorithms...
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A modified version of the Bezier-Bernstein polynomial approximation technique has been developed which gives local control of data points depending on an absolute error criterion. Based on this concept, two algorithms for coding a gray-tone image have been formulated. Error bounds have been developed which are used to approximate gray segments of pixels. These bounds are determined by the desired error in approximation. Effectiveness of the algorithms has been demonstrated on a set of images.
This paper re-examines modulated polyphase filter banks which use reverse-time subfilters to achieve perfect reconstruction and studies their performance for image coding when used to form a wavelet decomposition, To ...
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This paper re-examines modulated polyphase filter banks which use reverse-time subfilters to achieve perfect reconstruction and studies their performance for image coding when used to form a wavelet decomposition, To code the wavelet coefficients, we use the embedded zerotree wavelet (EZW) algorithm developed by Shapiro which is reasonably simple and yet achieves very good rate-distortion performance. The problem of eliminating filter transients is thoroughly studied here and optimal results are derived in both the absence and presence of subband coefficient quantization, Using this analysis as a starting point, we develop a new method of coding the filter states (required to eliminate edge transients) for transmission to the receiver which efficiently exploits interscale redundancy and is easily incorporated into the zerotree algorithm, Comparing this direct transmission method to circular convolution, we find that it achieves superior rate-distortion performance in a wide range of cases, coding comparisons between two infinite impulse response (IIR) wavelets and a number of biorthogonal wavelets are presented here. These comparisons indicate that the performance of the polyphase allpass wavelet is comparable to that of the best finite impulse response (FIR) biorthogonal wavelets with considerably reduced computational complexity.
A predictive image coder having minimal decoder complexity is presented, The image coder utilizes recursive interpolative DPCM in conjunction with adaptive classification, entropy-constrained trellis coded quantizatio...
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A predictive image coder having minimal decoder complexity is presented, The image coder utilizes recursive interpolative DPCM in conjunction with adaptive classification, entropy-constrained trellis coded quantization, and optimal rate allocation to obtain signal-to-noise ratios (SNR's) in the range of those provided by the most advanced transform coders.
In this paper, an adaptive image coding technique-two-channel conjugate classified discrete cosine transform/vector quantization (TCCCDCT/VQ)-is proposed to efficiently exploit correlation In large image blocks by tak...
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In this paper, an adaptive image coding technique-two-channel conjugate classified discrete cosine transform/vector quantization (TCCCDCT/VQ)-is proposed to efficiently exploit correlation In large image blocks by taking advantage of the discrete cosine transform and vector quantization while overcoming the suboptimalities of transform coding and reducing the complexity of vector quantization. Two-channel conjugate vector quantization (TCCVQ) has recently been proposed for speech coding [1]. Compared to the ordinary VQ, TCCVQ requires less computational complexity, less storage (memory) requirement and is more robust against channel errors. This technique has also recently been extended to image coding in the spatial domain [2]. This technique is now applied to image coding In the transform domain. In the transform domain, a classified discrete cosine transform/vector quantization (CDCT/VQ) scheme is proposed and TCCCDCT/VQ is developed based on the CDCT/VQ scheme. These two techniques are applied to encode test images at about 0.51 b/pixel and 0.73b/pixel. The performances of both techniques over a noisy channel have been also tested in the transform domain. The performances of both adaptive VQ techniques are perceptually very similar for the noise-free channel case. However, when channel error is injected for the same bit rate, The TCCCDCT/VQ gives subjectively much more pleasing (less visible distortion) images than the CDCT/VQ, which is based on ordinary VQ.
Wavelet transforms have recently emerged as powerful tools for data compression in image and video applications. Based on the strong interscale correlation between different scales on the same orientation and location...
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Wavelet transforms have recently emerged as powerful tools for data compression in image and video applications. Based on the strong interscale correlation between different scales on the same orientation and location in wavelet domain, a vector quantization coding scheme with a hierarchical codebook in wavelet domain is developed in this paper. The structure of the hierarchical codebook is designed and its training and construction criterion, based upon the conditional probability concept, is also described. Finally, the simulation results are presented.
In this correspondence, we address the problem of translation sensitivity of conventional wavelet transforms for two-dimensional (2-D) signals. We propose wavelet transform algorithms that achieve the following desira...
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In this correspondence, we address the problem of translation sensitivity of conventional wavelet transforms for two-dimensional (2-D) signals. We propose wavelet transform algorithms that achieve the following desirable properties simultaneously: i) translation invariance, ii) reduced edge effects, and iii) sice-limitedness. We apply this translation invariant biorthogonal wavelet transform with symmetric extensions to image coding applications with good results.
This paper deals with an image coding scheme based on overlapped projections and geometrical vector quantization. As far as still images are concerned, we present a simple coding algorithm, in which, the concept of pr...
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This paper deals with an image coding scheme based on overlapped projections and geometrical vector quantization. As far as still images are concerned, we present a simple coding algorithm, in which, the concept of projection, normally employed in tomographic applications, and geometric vector quantization are used to describe, in a compact way, circular overlapping regions in which the input image is subdivided. In this way it is possible to represent in a good way, contour and edge information without introducing significant blocking artefacts. The proposed coding techniques can also be used to represent images at progressive levels of quality. This aim can be simply obtained by increasing the number of projections used to describe each image region. Simulations carried out on several test images showed interesting results. An extension of this projection-based coding techniques is proposed for moving images too. In this case projections are used to describe in a compact way, the motion compensated luminance differences between the current image and the previous coded one. (C) 1997 Published by Elsevier Science B.V.
The authors describe and discuss the new technique, multistep adaptive flux interpolation (MAFI), and its application to image data for coding. When applied to an image, MAFI produces an output which is also in an ima...
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The authors describe and discuss the new technique, multistep adaptive flux interpolation (MAFI), and its application to image data for coding. When applied to an image, MAFI produces an output which is also in an image form, but which has a more uniform feature density and a greatly reduced size. MAFI warps the input image by removing those rows and columns which contain a majority of redundant pixels. The side information required for reconstruction is minimal, and the image can be further compressed using conventional coders, making the compression ratio even higher. Because of its warped nature, the MAFI output's statistics are also more consistent with the properties assumed by block-based discrete cosine transform (DCT) methods.
Proposed is a new algorithmic approach to segmentation-based image coding. A good compromise is achieve between segmentations by quadtree-based decomposition and by free region-growing in terms of time complexity and ...
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Proposed is a new algorithmic approach to segmentation-based image coding. A good compromise is achieve between segmentations by quadtree-based decomposition and by free region-growing in terms of time complexity and scene adaptability. Encoding is to recursively partition an image into convex n-gons, 3 less-than-or-equal-to n less-than-or-equal-to 8, until the pixels in current n-gon satisfy a uniformity criterion. The recursive partition generates a valid segmentation by aligning the polygon boundaries with image edges. This segmentation is embedded into a binary tree for compact encoding of its geometry. The compressed image is sent as a labeled pointerless binary tree, and decoding is simply polygon filling. High-compression ratios are obtained by balancing the accuracy and geometric complexity of the image segmentation;a key issue for segmentation-based image coding that was not addressed before. Due to its tree structure, the new method is also suitable for progressive image coding.
Based on importance measures and fuzzy integrals, a new assessment method for image coding quality is presented in this paper. The proposed assessment is based on two subevaluations. In the first subevaluation, errors...
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Based on importance measures and fuzzy integrals, a new assessment method for image coding quality is presented in this paper. The proposed assessment is based on two subevaluations. In the first subevaluation, errors on edges, textures, and flat regions are computed individually. The errors are then assessed using an assessment function. A global evaluation with Sugeno fuzzy integral is then obtained based on the importance measure of edge, texture, and flat region. In the second subevaluation, an importance measure is first established depending on the types of regions where errors occur, a subtle evaluation is then obtained using Sugeno fuzzy integral on all pixels of the image. A final evaluation is obtained based on the two subevaluations. Experimental results show that this new image quality assessment closely approximates human subjective tests such as mean opinion score with a high correlation coefficient of 0.963, which is a significant improvement over peak signal-to-noise ratio, picture quality scale, and weighted mean square error, three other image coding quality assessment methods, which have the correlation coefficients of 0.821, 0.875, and 0.716, respectively.
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