Codebook

About: Codebook is a research topic. Over the lifetime, 8492 publications have been published within this topic receiving 115995 citations.

Real-time vector excitation coding of speech at 4800 bps

Abstract: In Vector Excitation Coding (VXC), speech is represented by applying a sequence of excitation vectors to a time-varying speech production filter with each vector chosen from a codebook using a perceptually-based performance measure. Although VXC is a powerful technique for achieving natural and high quality speech compression at low bit-rates, it suffers as other excitation coders do from a very high computational complexity. Recent research has shown that codebook search computation can be reduced to approximately 40 MFlops without compromising speech quality. However, this operation count still prohibits a practical real-time implementation of the coder using today's DSP chips. We present a real-time 4.8 kb/s Pulse Excitation VXC coder (PVXC) which achieves high reconstructed speech quality and incorporates new techniques which reduce the codebook search complexity to only 0.55 MFlops. The coder utilizes an optimized excitation codebook and a promising new interframe vector predictive LPC parameter quantization scheme. A preliminary implementation using a single floating-point signal processor is described.

Video compression using adaptive variable length codes

Abstract: Adaptive variable length coding techniques may be used for entropy coding of residual block coefficients produced by predictive video coding. The techniques may be applied to schemes that code positions of nonzero transform coefficients using zero runs. Coding parameters such as end of block (EOB) shift and VLC codebook selection tables may be maintained as internal states, instead of sending them with coded video slice data. Table entries may be periodically updated based on statistics collected during a coding pass. A special EOB shift table may adapt the position of a special EOB symbol in a symbol set to probability of significant coefficients with magnitude greater than one for a coding condition, such as a coding cycle. Chroma blocks may be coded independently of luma blocks using separate EOB shift, special EOB shift, and VLC codebook selection tables.

USB: ultrashort binary descriptor for fast visual matching and retrieval.

Abstract: Currently, many local descriptors have been proposed to tackle a basic issue in computer vision: duplicate visual content matching. These descriptors either are represented as high-dimensional vectors relatively expensive to extract and compare or are binary codes limited in robustness. Bag-of-visual words (BoWs) model compresses local features into a compact representation that allows for fast matching and scalable indexing. However, the codebook training, high-dimensional feature extraction, and quantization significantly degrade the flexibility and efficiency of BoWs model. In this paper, we study an alternative to current local descriptors and BoWs model by extracting the ultrashort binary descriptor (USB) and a compact auxiliary spatial feature from each keypoint detected in images. A typical USB is a 24-bit binary descriptor, hence it directly quantizes visual clues of image keypoints to about 16 million unique IDs. USB allows fast image matching and indexing and avoids the expensive codebook training and feature quantization in BoWs model. The spatial feature complementarily captures the spatial configuration in neighbor region of each keypoint, hence is used to filter mismatched USBs in a cascade verification. In image matching task, USB shows promising accuracy and nearly one-order faster speed than SIFT. We also test USB in retrieval tasks on UKbench, Oxford5K, and 1.2 million distractor images. Comparisons with recent retrieval methods manifest the competitive accuracy, memory consumption, and significantly better efficiency of our approach.

Huffman coding of DCT coefficients using dynamic codeword assignment and adaptive codebook selection

Abstract: In many image sequence compression applications, Huffman coding is used to eliminate statistical redundancy resident in given data. The Huffman table is often pre-defined to reduce coding delay and table transmission overhead. Local symbol statistics, however, may be much different from the global ones manifested in the pre-defined table. In this paper, we propose three Huffman coding methods in which pre-defined codebooks are effectively manipulated according to local symbol statistics. The first proposed method dynamically modifies the symbol-codeword association without rebuilding the Huffman tree itself. The encoder and decoder maintain identical symbol-codeword association by performing the same modifications to the Huffman table, thus eliminating extra transmission overhead. The second method adaptively selects a codebook from a set of given ones, which produces the minimum number of bits. The transmission overhead in this method is the codebook selection information, which is observed to be negligible compared with the bit saving attained. Finally, we combine the two aforementioned methods to further improve compression efficiency. Experiments are carried out using five test image sequences to demonstrate the compression performance of the proposed methods.

Limited feedback precoding for spatial multiplexing systems using linear receivers

Abstract: Multiple-input multiple-output (MIMO) spatial multiplexing wireless systems achieve high spectral efficiencies by demultiplexing the incoming bit stream into multiple substreams. Spatial multiplexing is of practical importance because the multiple substreams can be decoded using linear receivers. Unfortunately, this reduction in complexity degrades the probability of error performance. To overcome this difficulty, error rate performance of spatial multiplexing systems can be improved by sending fewer substreams than the number of transmit antennas by linear preceding. Criteria have been proposed for designing these precoders when complete channel knowledge is available to the transmitter. The assumption of complete channel knowledge is often unrealistic in many communication systems such as those with low rate feedback channels. Thus a quantized preceding scheme is proposed where the receiver sends back a fixed number of bits to the transmitter. This bit pattern corresponds to an index within a finite set of preceding matrices. A previously proposed criterion is used to determine the matrix in this precoder codebook to choose. A design method for these codebooks using techniques from Grassmannian subspace packing is presented. Simulation results show this technique outperforms typical antenna selection.