Changhoon Yim

Layer-weighted unequal error protection for scalable video coding extension of H.264/AVC

The scalable video coding extension of H.264/AVC is a current standardization project. This paper deals with unequal error protection (UEP) scheme for scalable video bitstream over packet-lossy networks using forward error correction (FEC). The proposed UEP scheme is developed by exploiting jointly the unequal importance existing both in temporal layers and quality layers of hierarchial scalable video bitstream. For efficient assignment of FEC codes, the proposed UEP scheme uses a simple and efficient performance metric, namely layer-weighted expected zone of error propagation (LW-EZEP). The LW-EZEP is adopted for quantifying the error propagation effect on video quality degradation from packet loss in temporal layers and in quality layers. Compared to other UEP schemes, the proposed UEP scheme demonstrates strong robustness and adaptation for variable channel status.

Quality Assessment of Deblocked Images

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.

Evaluation of temporal variation of video quality in packet loss networks

We examine the effect that variations in the temporal quality of videos have on global video quality. We also propose a general framework for constructing temporal video quality assessment (QA) algorithms that seek to assess transient temporal errors, such as packet losses. The proposed framework modifies simple frame-based quality assessment algorithms by incorporating a temporal quality variance factor. We use packet loss from channel errors as a specific study of practical significance. Using the PSNR and the SSIM index as exemplars, we are able to show that the new video QA algorithms are highly responsive to packet loss errors.

Priority Tries for IP Address Lookup

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.

An efficient method for DCT-domain image resizing with mixed field/frame-mode macroblocks

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.

Efficient binary search for IP address lookup

As an essential function in Internet routers, address lookup determines overall router performance. The most important performance metric in software-based address lookup is the number of memory accesses since it is directly related to lookup time. This letter proposes an algorithm to perform efficient binary search for IP address lookup. The depth of the proposed binary tree is very close to the minimum bound, and hence it results in much smaller number of worst case memory accesses compared to previous schemes. The proposed algorithm requires comparably small size of memory, and it can be used for software-based address lookup in practical Internet routers.

Multiresolution 3-D range segmentation using focus cues

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.

Two-dimensional packet classification algorithm using a quad-tree

For the last few years, there is an explosive growth in the development and the deployment of network applications that transmit and receive audio and video over the Internet. In order for such multimedia applications to function properly, networks need to provide the level of performance, which is called the quality of services (QoS). An essential element for the Internet routers to provide the QoS is the packet classification which classifies incoming packets into classified flows. Based on the pre-defined rules composed of multiple header fields, incoming packets are classified into a specific flow, and packets are treated differently according to the classified flow. Efficient packet classification algorithms have been widely studied, but none of known algorithms except the linear search considers the priority of rules in constructing the data structure of classification tables. In this paper, we propose a priority-based quad-tree (PQT) algorithm for packet classification. In constructing a quad-tree generated based on recursive space decomposition, the priority of rules is primarily considered in the proposed algorithm. In the simulation using the class-bench databases, the proposed algorithm achieves very good performance in the required memory size and reasonable performance in the classification speed. The proposed algorithm also provides good scalability toward large classifiers.

Boundary cutting for packet classification

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.

IP address lookup for internet routers using balanced binary search with prefix vector

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.