503,785 research outputs found
Multiple Description Coding of Discrete Ergodic Sources
We investigate the problem of Multiple Description (MD) coding of discrete
ergodic processes. We introduce the notion of MD stationary coding, and
characterize its relationship to the conventional block MD coding. In
stationary coding, in addition to the two rate constraints normally considered
in the MD problem, we consider another rate constraint which reflects the
conditional entropy of the process generated by the third decoder given the
reconstructions of the two other decoders. The relationship that we establish
between stationary and block MD coding enables us to devise a universal
algorithm for MD coding of discrete ergodic sources, based on simulated
annealing ideas that were recently proven useful for the standard rate
distortion problem.Comment: 6 pages, 3 figures, presented at 2009 Allerton Conference on
Communication, Control and Computin
フラクタル符号化特徴量を用いた類似画像検索およびオブジェクト検出手法の検討
Fractal image coding is a block-based scheme that exploits the self-similarity hiding with an image. Fractal codes are quantitative measurements of the self-similarity of the image, and collage error distribution of block characterizes the degree of self-similarity in it. Furthermore, fractal codes can be used to obtain a practical image indexing system because of its compactness and stability. The most important reason using fractal codes is able to deal with the images in compressed form. Thus fractal indexing is suitable for use with large database. In this study, we propose a new image retrieval system and object detection method based on fractal coding features that are collage error distribution and block partition structure in fractal codes. Experimental results show that the proposed method achieves a high precision tracking which is faster than MPEG method
Convolutional Sparse Representations with Gradient Penalties
While convolutional sparse representations enjoy a number of useful
properties, they have received limited attention for image reconstruction
problems. The present paper compares the performance of block-based and
convolutional sparse representations in the removal of Gaussian white noise.
While the usual formulation of the convolutional sparse coding problem is
slightly inferior to the block-based representations in this problem, the
performance of the convolutional form can be boosted beyond that of the
block-based form by the inclusion of suitable penalties on the gradients of the
coefficient maps
Bilayer Protograph Codes for Half-Duplex Relay Channels
Despite encouraging advances in the design of relay codes, several important
challenges remain. Many of the existing LDPC relay codes are tightly optimized
for fixed channel conditions and not easily adapted without extensive
re-optimization of the code. Some have high encoding complexity and some need
long block lengths to approach capacity. This paper presents a high-performance
protograph-based LDPC coding scheme for the half-duplex relay channel that
addresses simultaneously several important issues: structured coding that
permits easy design, low encoding complexity, embedded structure for convenient
adaptation to various channel conditions, and performance close to capacity
with a reasonable block length. The application of the coding structure to
multi-relay networks is demonstrated. Finally, a simple new methodology for
evaluating the end-to-end error performance of relay coding systems is
developed and used to highlight the performance of the proposed codes.Comment: Accepted in IEEE Trans. Wireless Com
Model-independent rate control for intra-coding based on piecewise linear approximations
This paper proposes a rate control (RC) algorithm for intra-coded sequences (I-frames) within the context of block-based predictive transform coding that departs from using trained models to approximate the rate-distortion (R-D) characteristics of the video sequence. Our algorithm employs piecewise linear approximations of the rate-distortion (R-D) curve of a frame at the block-level. Specifically, it employs information about the rate and distortion of already compressed blocks within the current frame to linearly approximate the slope of the R-D curve of each block. The proposed algorithm is implemented in the High-Efficiency Video Coding (H.265/HEVC) standard and compared with its current RC algorithm, which is based on a trained model. Evaluations on a variety of intra-coded sequences show that the proposed RC algorithm not only attains the overall target bit rate more accurately than the RC algorithm used by H.265/HEVC algorithm but is also capable of encoding each I-frame at a more constant bit rate according to the overall bit budget
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