In this paper, a new wavelet transform image coding algorithm is presented. The discrete wavelet transform (DWT) is applied to the original image. The DWT coefficients are firstly quantized with a uniform scalar dead ...
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In this paper, a new wavelet transform image coding algorithm is presented. The discrete wavelet transform (DWT) is applied to the original image. The DWT coefficients are firstly quantized with a uniform scalar dead zone quantizer. Then the quantized coefficients are decomposed into four symbol streams: a binary significance map symbol stream, a binary sign stream, a position of the most significant bit (PMSB) symbol stream and a residual bit stream. An adaptive arithmetic coder with different context models is employed for the entropy coding of these symbol streams. Experimental results show that the compression performance of the proposed coding algorithm is competitive to other wavelet-based image coding algorithms reported in the literature. (C) 2006 Elsevier B.V. All rights reserved.
An entropy-constrained residual vector quantization design algorithm is used to design codebooks for image coding, Entropy-constrained residual vector quantization has several important advantages. It can outperform e...
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An entropy-constrained residual vector quantization design algorithm is used to design codebooks for image coding, Entropy-constrained residual vector quantization has several important advantages. It can outperform entropy-constrained vector quantization in terms of rate-distortion performance, memory, and computation requirements. It can also be used to design vector quantizers with relatively large vector sizes and high output rates. Experimental results indicate that good image reproduction quality can be achieved at relatively low bit rates, For example, a peak signal-to-noise ratio of 30.09 dB is obtained for the 512 x 512 image LENA at a bit rate of 0.145 b/p.
The blacking effect is a common problem that is always present in image coding when using blocking transform. A simple method for image coding, with low blacking effect using pre and post axis rotation and the discret...
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The blacking effect is a common problem that is always present in image coding when using blocking transform. A simple method for image coding, with low blacking effect using pre and post axis rotation and the discrete sine transform, is proposed in this work. It uses the overlap of only sample and the total number of transform coefficients remains the same as the number of pixel in the original image. The method was implemented, and the results obtained by simulation in the image coding are compared with image coding by DCT, DST, and LOT.
A new paradigm that combines data modeling and vector quantization in an effective coding technique is presented. We fit a statistical model to the input data and use the best fit parameters to synthesize training vec...
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A new paradigm that combines data modeling and vector quantization in an effective coding technique is presented. We fit a statistical model to the input data and use the best fit parameters to synthesize training vector sets with statistics similar to the input. By knowing the best-fit parameters, the decoder can synthesize the same training sets, while identical codebooks are obtained at both encoder and decoder based on the same codebook generation procedure. As a result, complete codebook adaptation is achieved with a very small increase in the bit rate. The implementation of the new technique in the transform domain produced competitive results when compared to other methods relying on vector quantization and transform coding. In particular, the image Lena was coded at 0.28 bits/pixel with a peak signal-to-noise ratio of 32.51 dB. (C) 2002 Elsevier Science B.V. All rights reserved.
The discrete wavelet transform has recently emerged as a powerful technique for decomposing images into various multi-resolution approximations. Multi-resolution decomposition schemes have proven to be very effective ...
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The discrete wavelet transform has recently emerged as a powerful technique for decomposing images into various multi-resolution approximations. Multi-resolution decomposition schemes have proven to be very effective for high-quality, low bit-rate image coding, In this work, we investigate the use of entropy-constrained trellis-coded quantization (ECTCQ) for encoding the wavelet coefficients of both monochrome and color images, ECTCQ is known as an effective scheme for quantizing memoryless sources with low to moderate complexity, The ECTCQ approach to data compression has led to some of the most effective source codes found to date for memoryless sources. Performance comparisons are made using the classical quadrature mirror filter bank of Johnston and nine-tap spline filters that were built from biorthogonal wavelet bases, We conclude that the encoded images obtained from the system employing nine-tap spline filters are marginally superior although at the expense of additional computational burden. Excellent peak-signal-to-noise ratios are obtained for encoding monochrome and color versions of the 512 x 512 ''Lenna'' image, Comparisons with other results from the literature reveal that the proposed wavelet coder is quite competitive.
The conception of digital image coding techniques is of great interest in various areas concerned with the storage or transmission of images. For the past few years, there has been a tendency to combine different clas...
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The conception of digital image coding techniques is of great interest in various areas concerned with the storage or transmission of images. For the past few years, there has been a tendency to combine different classical coding techniques in order to obtain greater coding efficiency. In this paper, we propose an independent and novel approach to image coding, based on a fractal theory of iterated transformations. The main characteristics of this approach are that i) it relies on the assumption that image redundancy can be efficiently exploited through self-transformability on a block-wise basis, and ii) it approximates an original image by a fractal image. We, therefore, refer to our approach as fractal block coding. The coding-decoding system is based on the construction, for an original image to encode, of a specific image transformation-a fractal code-which, when iterated on any initial image, produces a sequence of images which converges to a fractal approximation of the original. We show how to design such a system for the coding of monochrome digital images at rates in the range of 0.5-1.0 b/pixel. Our fractal block coder has performance comparable to state-of-the-art vector quantizers, with which it shares some aspects. Extremely promising coding results are obtained.
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.
A novel coding algorithm for binary images based on neighbourhood relations is used for the problem of handwritten numerals recognition. Each pixel of an image is transformed into a set of representative vectors by co...
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A novel coding algorithm for binary images based on neighbourhood relations is used for the problem of handwritten numerals recognition. Each pixel of an image is transformed into a set of representative vectors by coding it according to the number of neighbours in the four directions (north, east, south, west). These neighbourhood vectors are transformed into a set of codes satisfying the boundary condition imposed by the size of the image in which the shape is embedded. A code reduction function is used for the purpose of information reduction and generalization of the shape images. Using the digits of the NIST handwritten segmented characters set, we show an application of the neighbourhood coding for pattern recognition. (C) 1999 Elsevier Science B.V. All rights reserved.
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.
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.
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