Hierarchical image coding usually codes a down-sampled version of an original image and then the difference between the original image and a reconstructed version that is interpolated from the down-sampled layer. In t...
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Hierarchical image coding usually codes a down-sampled version of an original image and then the difference between the original image and a reconstructed version that is interpolated from the down-sampled layer. In this paper, we demonstrate, for the first time, that when the bit-rate used to code the residual layer falls into a critical region (which covers almost all typical bit-rates used in practice), it often happens that all pixels in the down-sampled layer would be deteriorated if the corresponding coded residuals are added into them. To avoid this problem, we first propose a "naive" solution: no coded residuals will be added back into the down-sampled layer;whereas coded residuals will be added only into the interpolated pixels. Then, we propose to apply a constrained quantization technique during the coding of the residual layer so that all residual pixels at the interpolated positions will end up with an improved quality. To verify its effectiveness, we conduct extensive tests to show that the gap between the hierarchical coding scheme and its single-level counterpart (which is typically around 2-3 dB in the 2-level hierarchy) will be filled up by a rather big percentage. (C) 2012 Elsevier Inc. All rights reserved.
In this paper, window design and fast algorithm for the overlapping block transform (OBT) of size NxL are presented, The presented algorithm for the OBT reduces the calculation complexity to an NxN transform with a fa...
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In this paper, window design and fast algorithm for the overlapping block transform (OBT) of size NxL are presented, The presented algorithm for the OBT reduces the calculation complexity to an NxN transform with a fast algorithm and a simple preprocessing including windowing, A signal-independent window optimization strategy is introduced for image coding application, Results for a first-order Markov model and an image coding experiment show, that the coding gains of the optimized OBT's increase and blocking effects decrease with increasing window length L. A comparison with DCT-coding shows that the OBT, whch has a slightly increased realization complexity, provides higher coding gain and a significant blocking effect reduction.
A computationally efficient image compression technique is presented, which is based on visual patterns as well as least squares fractal approximation by a Self Affine System (SAS). Simulation studies demonstrate that...
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A computationally efficient image compression technique is presented, which is based on visual patterns as well as least squares fractal approximation by a Self Affine System (SAS). Simulation studies demonstrate that the use of visual pattern-based technique can code the shade (nat) regions of an image more efficiently than fractal techniques. Furthermore, the proposed technique not only gives encoding speed several times faster than other SAS-based fractal coding techniques but also achieves higher compression ratios and better fidelity.
Traditional 2-D discrete cosine transform (DCT) implemented by separable I-D transform in horizontal and vertical directions does not take image orientation features in a local window into account. To improve it, we p...
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Traditional 2-D discrete cosine transform (DCT) implemented by separable I-D transform in horizontal and vertical directions does not take image orientation features in a local window into account. To improve it, we propose to introduce directional primary operations to the lifting-based DCT and thereby derive a new directional DCT-like transform, whose transform matrix is dependent on directional angle and interpolation used there. Furthermore, the proposed transform is compared with the straightforward one of first rotated and then transformed. A JPEG-wise image coding scheme is also proposed to evaluate the performance of the proposed directional DCT-like transform. The first 1-D transform is performed according to image orientation features, and the second 1-D transform still in the horizontal or vertical direction. At the same time, an approach is proposed to optimally select transform direction of each block because selected directions of neighboring blocks will influence each other. The experimental results show that the performance of the proposed directional DCT-like transform can dramatically outperform the conventional DCT up to 2 dB even without modifying entropy coding.
A nonseparable pyramid method based on a wavelet ex. pansion Is developed for image coding. It achieves high compression rates and at the same time it allows a very efficient algorithmic Implementation. In particular ...
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A nonseparable pyramid method based on a wavelet ex. pansion Is developed for image coding. It achieves high compression rates and at the same time it allows a very efficient algorithmic Implementation. In particular it uses only two additions and a shift (division by 2) for each image pixel during coding or decoding. Because the operations needed are mostly independent of each other and have a high degree of regularity, it is also possible to design very-large-scale integration (VLSI) hardware to perform this operation using an array of simple basic cells. For a typical 513 x 513 image we can achieve a peak signal-to-noise ratio of 30 dB with an entropy of 0.133 b/pixel. Transmitted coefficient values can be encoded with PCM, to allow for simpler hardware while still requiring only 0.385 b/pixel, giving a very simple overall coding system.
We introduce a novel, adaptive image representation using spatially varying wavelet packets (WP's). Our adaptive representation uses the fast double-free algorithm introduced in [1] to optimize an operational rate...
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We introduce a novel, adaptive image representation using spatially varying wavelet packets (WP's). Our adaptive representation uses the fast double-free algorithm introduced in [1] to optimize an operational rate-distortion (R-D) cost function, as is appropriate for the lossy image compression framework. This involves jointly determining which filter bank tree (WP frequency decomposition) to use, and when to change the fitter bank tree (spatial segmentation). For optimality, the spatial and frequency segmentations must be done jointly, not sequentially. Due to computational complexity constraints, we consider quadtree spatial segmentations and binary WP frequency decompositions (corresponding to two-channel filter banks) for application to image coding. We present results verifying the usefulness and versatility of this adaptive representation for image coding using both a first-order entropy rate-measure-based coder as well as a powerful space-frequency quantization-based (SFQ-based) wavelet coder introduced in [11].
Octave subband coding has been used as an efficient image coding approach for various well-known standards such as MPEG-4 and JPEG-2000. Although the sub-images in the octave subband representation have low statistica...
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Octave subband coding has been used as an efficient image coding approach for various well-known standards such as MPEG-4 and JPEG-2000. Although the sub-images in the octave subband representation have low statistical correlation, the visual similarity among the sub-images indicates that there exists some unexploited perceptual redundancy between sibling bands in addition to the parent-child redundancy. In this paper, we show that the original image can be perceptually dithered to form a visually equivalent image with increased interband correlation that can be used to achieve more compression. To remove the redundancy among the sibling subbands of an image, we provide a novel perceptual dithering approach that is based on entropy reduction technique with perceptual model. The theoretical basis for the entropy reduction is proven by a theorem for Gaussian distributed signals. The use of our dithering technique is demonstrated for an MPEG-4 compliant encoder with improved coding efficiency using MPEG-4 Visual Texture coding (VTC) based on zerotree entropy coding. Our results show that there exists a perceptual interband redundancy even though the original interband correlation is small. For a perceptually transparent image quality, our approach can achieve bit savings over MPEG-4 VTC by 11-30%, while maintaining compatibility with the MPEG-4 standards. (C) 2003 Elsevier Inc. All rights reserved.
Removing perceptual redundancy plays an important role in image compression. In this paper we develop a foveated just-noticeable-difference (FJND) model to quantify the perceptual redundancy in the image and integrate...
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Removing perceptual redundancy plays an important role in image compression. In this paper we develop a foveated just-noticeable-difference (FJND) model to quantify the perceptual redundancy in the image and integrate it in the H.265/HEVC intra encoding framework to provide a perceptually lossless image coding solution. Different to the conventional JND models, our proposed FJND model considers the relationship between contrast masking effect and the foveation properties of HVS. Furthermore, to achieving the perceptually lossless coding, the FJND model is integrated in the H.265/HEVC framework by determining the quantization parameter to ensure that the resulting distortion is no larger than the FJND threshold. The experiments demonstrate that the proposed method effectively improves the compression performance. (C) 2016 Elsevier Inc. All rights reserved.
Recently, a new class of image coding algorithms coupling standard scalar quantization of frequency coefficients with tree-structured quantization (related to spatial structures) has attracted wide attention because i...
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Recently, a new class of image coding algorithms coupling standard scalar quantization of frequency coefficients with tree-structured quantization (related to spatial structures) has attracted wide attention because its good performance appears to confirm the promised efficiencies of hierarchical representation [1], [2]. This paper addresses the problem of how spatial quantization modes and standard scalar quantization can be applied in a jointly optimal fashion in an image coder. We consider zerotree quantization (zeroing out tree-structured sets of wavelet coefficients) and the simplest form of scalar quantization (a single common uniform scalar quantizer applied to all nonzeroed coefficients), and we formalize the problem of optimizing their joint application. We develop an image coding algorithm for solving the resulting optimization problem, Despite the basic form of the two quantizers considered, the resulting algorithm demonstrates coding performance that is competitive, often outperforming the very best coding algorithms in the literature.
The resource-constrained camera integrated Visual Sensor Networks (VSN) have conquered numerous visual aided services from visual surveillance to habitat monitoring. VSN is capable of sensing, processing and communica...
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The resource-constrained camera integrated Visual Sensor Networks (VSN) have conquered numerous visual aided services from visual surveillance to habitat monitoring. VSN is capable of sensing, processing and communicating visual data wirelessly. These networks are built with inexpensive low power sensor motes with a lightweight processor, limited storage, and bandwidth. The huge amount of redundancy present in the images makes the processing and communication consume more energy than expected. The number of bits must be reduced using energy-efficient compression techniques for efficient transmission. Low computational energy and communication energy are always favored for an increased lifetime of the wireless sensor network. The highly sensitive and self-descriptive nature of images makes security in VSN even more critical. In this work, we propose an energy-efficient low bitrate secured image coder for resource-constrained VSN. Light weight design protocols are highly required in secured image transmission over VSN. Through this communication, we also propose a novel chaotic map using Pascal's triangle. The system follows a unique interleaved fashion of compression and encryption process to consume less computational resources. A series of tests were carried out to validate the secured image coder's ruggedness and its suitability in VSN. The performance and the strength of the low bitrate secured image coder are tested with compression efficiency and cryptanalysis tests. Simulations were carried out in Atmel's ATmega128 processor for energy consumption analysis. The energy consumed by the proposed system for compression, encryption and transmission of an image of size 512 x 512 is 109.364mJ (milli Joules), which is only 4.57 % of the energy consumed by raw image transmission. In addition, the system is implemented in real time image sensor platform based on Arduino Due board integrated with OV7670 camera module for real time verification and the experimental result
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