37975436
Complexity-Distortion Optimal Search Algorithm for Block Motion Estimation
13282723
A cascading MRVQ-DCT scheme for the compression of sequence images
In this correspondence, a mean residual vector quantizer (MRVQ) is superimposed on the motion estimator for improving the intraframe coding quality of MPEG. The proposed scheme performs an MRVQ before executing the discrete cosine transformation (DCT) for the purpose of curing the DCT intrinsic trouble of blocking effect at low bit rate.
1269749
Complexity-adaptive search algorithm for block motion estimation
We propose a complexity-adaptive fast block matching algorithm design strategy that allows the user to terminate the algorithm at any target computational complexity. Two complexity-adaptive techniques, frame level complexity allocation and block level complexity allocation, are developed to approach the global complexity-distortion optimization A buffer control strategy is proposed to dynamically adjust the target complexity of one frame. The predictive complexity-distortion benefit list (PCDB list) technique is employed to allocate the target complexity into each block. By these techniques, we modify the full-search block matching, three-step search, new three-step search, and four-step search to the complexity-adaptive algorithms. Experimental results show that the complexity-adaptive algorithms could achieve better performance than traditional fixed algorithms from the viewpoint of complexity-distoftion optimization.
28811627
Recognizing depth-first-search trees in parallel
Consider that T. is a given spanning tree of an undirected graph G which contains a vertices and m (/spl ges/n-1) edges. In this paper, we propose an O(m/p+log m)-time parallel algorithm using p processors on the EREW PRAM model to determine whether T is a depth-first-search tree of G. Our algorithm is optimal in time complexity and speed-up.<<ETX>>
29712526
Three-sided side match finite-state vector quantization
Several low bit-rate still-image compression methods have been presented, such as SPHIT, hybrid VQ, and the Wu-Chen (see Proc. IEEE ICASSP, 1997) method. In particular, the image "Lena" can be compressed using less than 0.15 bpp at 31.4 dB or higher. These methods exercise the analysis techniques (wavelet or subband) before distributing the bit rate to each piece of an image, thus the dilemma between bit rate and distortion can be solved. In this paper, we propose a simple but comparable method that adopts the technique of side match VQ only. The side match vector quantization (SMVQ) is an effective VQ coding scheme at low bit-rate. The conventional side match (two-sided) VQ utilizes the codeword information of two neighboring blocks to predict the state codebook of an input vector. We propose a hierarchical three-sided side match finite-state vector quantization (HTSMVQ) method that can: (1) make the state codebook size as small as possible-the size is reduced to one if the prediction can perform perfectly; (2) improve the prediction quality for edge blocks; and (3) regularly refresh the codewords to alleviate the error propagation of side match. In the simulation results, the image "Lena" can be coded with a PSNR 34.682 dB at 0.25 bpp. It is better than SPIHT, EZW, FSSQ and hybrid VQ with 34.1, 33.17, 33.1, and 33.7 dB, respectively. At a bit rate lower than 0.15 bpp, only the enhanced version of EZW performs better than our method, at about 0.14 dB.
39144227
Cursive word reference line detection
This paper proposes a novel method in detecting the four reference lines of a cursive word at any skew angle. The proposed method is rotation independent because the detection is based on points determined by their relative positions between the outer contour of a cursive word and its convex hull. Features like bounding box, contour area, convex hull and furthest points are used in detecting and grouping these points. The reference lines are detected by searching for suitable peaks in the Hough transformation space of these points. Encouraging experimental results have been obtained.
5763734
Finding approximate patterns in undirected acyclic graphs
Abstract We consider an approximate pattern matching problem for undirected acyclic graphs. Specifically, let P be a pattern graph, D a data graph and t an integer. We present an algorithm to locate a subgraph in D whose distance from P is at most t . The distance measure used here is the degree-2 metric published previously. The time complexity of our algorithm is O(N P N D d d log d) where N P and N D are the number of nodes in P and D , respectively; d =min{ d P , d D }; d P and d D are the maximum degree of P and D , respectively. Central to our algorithm is a procedure for finding approximate patterns in rooted unordered trees and freely allowing cuts. We discuss two applications of the algorithms in chemical information search and website management on the Internet.
15536346
An Index Structure for Data Mining and Clustering
Abstract. In this paper we present an index structure, called MetricMap, that takes a set of objects and a distance metric and then maps those objects to a k-dimensional space in such a way that the distances among objects are approximately preserved. The index structure is a useful tool for clustering and visualization in data-intensive applications, because it replaces expensive distance calculations by sum-of-square calculations. This can make clustering in large databases with expensive distance metrics practical. We compare the index structure with another data mining index structure, FastMap, recently proposed by Faloutsos and Lin, according to two criteria: relative error and clustering accuracy. For relative error, we show that (i) FastMap gives a lower relative error than MetricMap for Euclidean distances, (ii) MetricMap gives a lower relative error than FastMap for non-Euclidean distances (i.e., general distance metrics), and (iii) combining the two reduces the error yet further. A similar result is obtained when comparing the accuracy of clustering. These results hold for different data sizes. The main qualitative conclusion is that these two index structures capture complementary information about distance metrics and therefore can be used together to great benefit. The net effect is that multi-day computations can be done in minutes.
62569135
Clustering for processing rate optimization
Clustering (or partitioning) is a crucial step between logic synthesis and physical design in the layout of a large scale design. A design verified at the logic synthesis level may have timing closure problems at post-layout stages due to the emergence of multiple-clock-period interconnects. Consequently, a trade-off between clock frequency and throughput may be needed to meet the design requirements. In this paper, we find that the processing rate, defined as the product of frequency and throughput, of a sequential system is upper bounded by the reciprocal of its maximum cycle ratio, which is only dependent on the clustering. We formulate the problem of processing rate optimization as seeking an optimal clustering with the minimal maximum-cycle-ratio in a general graph, and present an iterative algorithm to solve it. Since our algorithm avoids binary search and is essentially incremental, it has the potential of being combined with other optimization techniques. Experimental results validate the efficiency of our algorithm.
40322050
Complete on Average Boolean Satisfiability
Abstract We present in this paper a dynamic binary coding scheme α on CNF formulas ψ , and show that under a uniform distribution μ α on binary string α ( ψ ), SAT is complete on average, where μ α ( ψ ) is proportional to ∣ α ( ψ )∣ −2 2 −∣ α ( ψ )∣ . We then show that there is k 0 >2 such that for all k ⩾ k 0 , k SAT under μ α is complete on average.