This paper proposes a novel video error concealment method for the reconstruction of all unknown regions in frames. The proposed method first performs temporal error concealment (TEC) sequentially in forward direction with the propagation of source information for the unknown regions of frames in group-of-frames (GOF). Then, it performs the TEC sequentially in backward direction for the remaining unknown regions in the GOF. For the reconstruction of unknown regions in each target frame in forward and backward TEC stages, we propose an adaptive homography-based registration of the reference frame. The proposed method selects adaptively global or local homography-based registration for the reconstruction of each unknown region. After the backward direction, the TEC is performed in each frame and the spatial error concealment is applied to reconstruct completely the remaining unknown regions with relatively small sizes. The experimental results show that the proposed method gives significantly improved objective and subjective video quality compared with the traditional reconstruction methods. The proposed method also gives comparably good reconstruction results for large size unknown regions and is feasible for practical real-time applications.

Decision-tree-based packet classification algorithms such as HiCuts, HyperCuts, and EffiCuts show excellent search performance by exploiting the geometrical representation of rules in a classifier and searching for a geometric subspace to which each input packet belongs. However, decision tree algorithms involve complicated heuristics for determining the field and number of cuts. Moreover, fixed interval-based cutting not relating to the actual space that each rule covers is ineffective and results in a huge storage requirement. A new efficient packet classification algorithm using boundary cutting is proposed in this paper. The proposed algorithm finds out the space that each rule covers and performs the cutting according to the space boundary. Hence, the cutting in the proposed algorithm is deterministic rather than involving the complicated heuristics, and it is more effective in providing improved search performance and more efficient in memory requirement. For rule sets with 1000-100 000 rules, simulation results show that the proposed boundary cutting algorithm provides a packet classification through 10-23 on-chip memory accesses and 1-4 off-chip memory accesses in average.

We study the efficiency of deblocking algorithms for improving visual signals degraded by blocking artifacts from compression. Rather than using only the perceptually questionable PSNR, we instead propose a block-sensitive index, named PSNR-B, that produces objective judgments that accord with observations. The PSNR-B modifies PSNR by including a blocking effect factor. We also use the perceptually significant SSIM index, which produces results largely in agreement with PSNR-B. Simulation results show that the PSNR-B results in better performance for quality assessment of deblocked images than PSNR and a well-known blockiness-specific index.

High-speed IP address lookup is essential to achieve wire speed packet forwarding in Internet routers. The longest prefix matching for IP address lookup is more complex than exact matching because it involves dual dimensions: length and value. This paper presents a new formulation for IP address lookup problem using range representation of prefixes and proposes an efficient binary trie structure named a priority trie. In this range representation, prefixes are represented as ranges on a number line between 0 and 1 without expanding to the maximum length. The best match to a given input address is the smallest range that includes the input. The priority trie is based on the trie structure, with empty internal nodes in the trie replaced by the priority prefix which is the longest among those in the subtrie rooted by the empty nodes. The search ends when an input matches a priority prefix, which significantly improves the search performance. Performance evaluation using real routing data shows that the proposed priority trie is very good in performance metrics such as lookup speed, memory size, update performance, and scalability.

We propose an efficient binary search algorithm for IP address lookup in the Internet routers. While most of the previous binary search algorithms do not provide a balanced search, the proposed algorithm provides a perfectly balanced search, and hence it provides excellent search performance and scalability toward large routing tables.

This paper proposes an algorithm managing the end-to-end video distortion of all users in multiuser orthogonal frequency division multiplex (OFDM) systems. The proposed algorithm mainly exploits the unequal importance of transmitted video packets and the diversity of multiuser existing in sub-carriers. We firstly induce model based rate-distortion function for measuring the amount of video quality degradation which a video packet affects in a group of picture (GOP). Based on the information of distortion in a packet to be transmitted, we propose the distortion management algorithm to allocate resources to users by balancing the subcarriers and power usages. Compared to the previous TDMA, simulation results show that substantial improvements of video quality are achieved.

Error concealment (EC) has been adopted to reconstruct lost information for video transmission over wireless networks. For intra-frame EC in H.264 video, only spatial correlations between neighboring macroblocks have been applied for spatial interpolation of the lost macroblock. In this paper, we first propose a simple temporal EC,which uses the temporal correlations between neighboring frames and improves the EC performance for intra-frame in H.264. Then we propose a new hybrid EC method for intra-frame in H.264, which combines the spatial EC and the temporal EC adaptively. Simulation results show that the proposed temporal EC shows substantial PSNR improvement compared to the previous spatial EC in H.264 intra-frame when the amount of motion is small. The proposed hybrid EC achieves further PSNR improvement compared to the temporal ECwhen the amount of motion is rather large.

We propose an efficient method for separable symmetric linear filtering in the discrete cosine transform (DCT) domain. First, separable two-dimensional (2-D) linear filtering is decomposed into the cascade of one-dimensional filtering in the DCT domain. We investigate special characteristics of DCT domain filtering matrices when the filter coefficients are symmetric. Then we present the DCT-domain 2-D filtering method using these characteristics. The proposed method requires a smaller number of multiplications including the typical sparseness of DCT coefficients compared to previous DCT-domain linear filtering methods. Also, the proposed method is composed of simple and regular operations, which would be appropriate for efficient very large scale integration implementation.

MPEG-1 layer-3, popularly known as MP3, has revolutionized the digital music domain. MP3 makes use of psychoacoustic modeling to achieve compression through the removal of perceptually irrelevant components of digital audio. The psychoacoustic model is the key element of perceptual coding and requires intensive FFT computation for calculating the frequency spectrum. This spectrum is used to compute masking thresholds. Thus, the original MP3 algorithm computes modified discrete cosine transform (MDCT) and FFT parallelly. The proposed algorithm is an alternative to this. We make use of complex modified discrete cosine transform (CMDCT) of the filter-bank outputs for generating MDCT coefficients as well as the frequency spectrum. This method requires fewer computations than the original method. A novel method of window switching, based on filter-bank output is used to simplify the overall algorithm. The proposed algorithm reduces the amount of computations for MP3 encoder while retaining the audio quality.

This paper deals with the discrete cosine transform (DCT)-domain image resizing as compressed domain processing. Previous DCT-domain image resizing methods assume that all macroblocks are in the frame-mode. We propose an efficient method for DCT-domain image resizing with mixed field/frame-mode macroblocks. This method is developed from the investigation of the DCT-domain image resizing operation through a decomposition of matrix operations, from which we define new downsampling matrices for frame- and field-mode macroblocks. This leads to new frame- and field-mode resizing transformation matrices for DCT-domain image resizing. The proposed DCT-domain image resizing method can be used when there are mixed field/frame-mode macroblocks.

This paper describes a novel system for computing a three-dimensional (3-D) range segmentation of an arbitrary visible scene using focus information. The process of range segmentation is divided into three steps: an initial range classification, a surface merging process, and a 3-D multiresolution range segmentation. First, range classification is performed to obtain quantized range estimates. The range classification is performed by analyzing focus cues within a Bayesian estimation framework. A combined energy functional measures the degree of focus and the Gibbs distribution of the class field. The range classification provides an initial range segmentation. Second, a statistical merging process is performed to merge the initial surface segments. This gives a range segmentation at a coarse resolution. Third, 3-D multiresolution range segmentation (3-D MRS) is performed to refine the range segmentation into finer resolutions. The proposed range segmentation method does not require initial depth estimates, it allows the analysis of scenes containing multiple objects, and it provides a rich description of the 3-D structure of a scene.

This paper presents a fixed-point error analysis for the unified systolic array implementation of 2-dimensional (2-D) discrete cosine transform (DCT) and 2-D inverse discrete cosine transform (IDCT). Closed form expressions for the mean and variance of fixed-point rounding-errors and truncation-errors are derived. Simulation results are provided to verify the analysis. Simulations designed to find the minimum word-length which satisfies IEEE requirements for the implementation of an 8/spl times/8 IDCT are also performed. Simulation results show that the proposed systolic array is more robust for the fixed-point error than other existing implementations for DCT/IDCT.

The objective of range segmentation is to partition a scene into regions with different depth ranges. We first perform range classification by combining two paradigms: focus cues and Bayesian estimation. A criterion function from focus cues provides a basic rule for measuring the ranges of a region in images. A Bayesian estimation is obtained by modeling the class field as a Markov random field (MRF). To combine these two paradigms, we define a combined energy function in terms of the cost function using the criterion function values for focus measure and the energy function of the Gibbs distribution of the class field. Then the combined energy function is minimized by a modified simulated annealing method to obtain range classification. The range classification is based on quantized ranges, and it provides an initial range segmentation. For range segmentation, we obtain interpolated range values, and perform a merging process by modeling the field of ranges as a Gaussian Markov random field. The range segmentation result gives a description of the 3-D structure of a scene.