Jia-Shung Wang

Adaptive fast block-matching algorithm by switching search patterns for sequences with wide-range motion content

Content with rapid, moderate, and slow motion is frequently mixed together in real video sequences. Until now, no fast block-matching algorithm (FBMA), including the well-known three-step search (TSS), the block-based gradient descent search (BBGDS), and the diamond search (DS), can efficiently remove the temporal redundancy of sequences with wide range motion content. This paper proposes an adaptive FBMA, called A-TDB, to solve this problem. Based on the characteristics of a proposed predicted profit list, the A-TDB can adaptively switch search patterns among the TSS, DS, and BBGDS, according to the motion content. Experimental results reveal that the A-TDB successfully adopts the search patterns to remove the temporal redundancy of sequences with slow, moderate and rapid motion content.

Image sequence coding using adaptive tree-structured vector quantization with multipath searching

A new adaptive tree-structured vector quantization (adaptive TSVQ) with multipath searching is described. The structure of the codebook tree is reorganized at an update interval, without requiring any transmission of side information. The 1-path tree searching algorithm is the simple way to find the closest codeword in TSVQ. But the disadvantage of 1-path searching is that the selected codeworks are not, in general, closest to the input vectors. Hence, the authors propose the multipath searching algorithm to improve the image quality. In an experiment, the improvement over the fixed TSVQ at the same bit rate is up to 2.03 dB when the number of the leaves in the codebook tree is 256 and 4-path searching is applied.<<ETX>>

Efficient motion-vector-based video search using query by clip

In this paper, a simple and efficient motion-vector-based search engine supporting query by clip is presented for indexing and retrieving of videos. We propose a technique to filter and reconstruct noisy motion vectors to improve the fidelity of the motion activity. In addition to the motion features of intensity and direction, a new motion descriptor, named representative spectrum, extracted by a vector quantization expressing the spatial-temporal distribution of motion activity, is introduced for video indexing. A dynamic programming scheme is also utilized to measure the similarity of two videos based on the concept of common subsequence. Furthermore, a 2-step search of similar videos is employed to reduce the computational complexity. The experimental results indicate that the proposed search engine performs well and the obtained recall and precision values are also high enough

Unequal-Protected LT Code for Layered Video Streaming

In this paper, we proposed a channel coding mechanism for layered videos based on the concept of Luby-Transform (LT) code. In a layered video streaming system, every video layer suffers from equal packet-loss rate; however, lower layers are more important than the higher ones. The proposed mechanism can protect those important layers from packet-loss to some meaningful degree. In other words, lower video layers can be earlier and easier decoded than high layers under the same packet-loss rate. Compared with other Unequal Error Protection schemes using Reed-Solomon code or LT code, the complexity and overhead are largely reduced. Besides, a randomized implement to generate appropriate coding graph on-line was proposed also, thus our mechanism is suitable for real-time applications with devices of limited computation capability and stringent delay requirement.

An embedded merging scheme for H.264/AVC motion estimation

The emerging H.264/AVC video coding standard takes 50% performance improvement than the H.263. One of the key successful factors is to employee the variable block size matching algorithm in the motion compensation stage. However, the highly computational complexity leads the codec become too complex and hard to implement in some real time applications. Again, large memory requirement to save the middle results limits its usage, too. In this paper, we proposed an embedded merging scheme for fast full search algorithm of H.264/AVC. The proposed scheme cannot only reduce the computation complexity but also provides a better way to be implemented in VLSI hardware.

Region-based fractal image compression with quadtree segmentation

Fractal image coding is a novel technique for still image compression. A low bit rate region-based fractal image compression algorithm is proposed and several techniques are included as follows. First, we improve the performance of quadtree segmentation by an adaptive threshold. Then, a merging scheme is employed to the resulting quadtree segmentation that combines several similar blocks into a small number of regions. We also provide a quadtree-based segmented chain code to efficiently record the contours of the regions. The experimental results show that the proposed scheme has the lowest bit rate among the existing schemes at the same level of image quality.

Data Aggregation with Spatially Correlated Grouping Technique on Cluster-Based WSNs

Wireless sensor networks have received considerable attention in recent years due to their invaluable potential applications. To achieve long-term deployment, in-network aggregation has been studied and argued as an effective data reduction technique. In this paper, an efficient algorithm to construct and maintain aggregation architecture in cluster-based sensor networks, such as LEACH, is proposed. The architecture takes the spatial and temporal correlations among nodes into account simultaneously to develop the suppression strategies. The main idea is to organize nodes inside the same cluster into highly spatial-correlated groups. One representative node of each group will be selected as base node used as a reference for compressing (using linear regression) the transmissions of the nodes inside the same group. The proposed architecture was evaluated on the real dataset, Intel Lab dataset, and the results indicate that a large amount of transmissions can be reduced without introducing large errors. In contrast to the existing aggregation architectures, such as TAG and TiNA, the results also portray that the hybrid architecture can perform better by considering both spatial and temporal correlations simultaneously.

Error resilience supporting bi-directional frame recovery for video streaming

In this paper, we propose a novel coding dependency among video frames which supports efficient error resilience without adding any redundancy. Our approach is based upon reorganizing the regular GOP structure. The proposed scheme can effectively recover a lost frame and prevent the error propagation phenomenon. For a single frame loss, we guarantee that both of its next and previous frames still can be successfully decoded, thus we have sufficient temporal and spatial information to reconstruct the damaged frame. Our new coding structure even can recover successive lost frames. The experimental results showed that the video quality has a graceful degradation when the loss rate increases rapidly. Comparing with the conventional GOP, PSNR values can improve from 0.5 dB to 3 dB.

Adaptive post-processing for region-based fractal image compression

Summary form only given. Region-based fractal image compression (Chang et al., 1997) is an attractive variation of fractal image compression algorithm. By segmenting an image into variable sizes of quadtree blocks and then merging these blocks into regions, this algorithm has the potential to encode a still image with a very low bit rate. However, highly visible artifacts become annoying when the coding bit rate is low. A large number of studies have been done in the literature to improve the reconstructed image quality at low bit rates. In this paper, an adaptive image enhancement algorithm for region-based fractal image compression is proposed. By utilizing an algorithm to determine which pixels have to be smoothed, then applying different smoothing filters for various image areas, the proposed algorithm can significantly eliminate the annoying blocking artifacts for images coded with low bit rate.

A New Series Resistance and Mobility Extraction Method by BSIM Model for Nano-Scale MOSFETs

In this work, a simplified BSIM-based model has been proposed to solve the above issues contributed by halo implants [Goto, K, et al., 2003]. In this new methodology, R_sd and mu_eff can be uniquely extracted in nano-scale devices. Furthermore, the extracted L_G dependency of mu_eff may serve as a good indicator for monitoring the relationship between geometry and stress parameters