17351609
Two-dimensional LMS adaptive linear phase filters
Two-dimensional least mean square (2D LMS) adaptive filters are used in image processing applications for reducing noise. A new two-dimensional LMS algorithm is proposed, in which an additional linear phase constraint is added to the constraints of the existing 2D LMS algorithms. Compared with the conventional algorithms, the results show that the proposed algorithm is much more efficient both in computation time and memory storage.<<ETX>>
10271144
Robust image authentication method surviving JPEG lossy compression
Image authentication verifies the originality of an image by detecting malicious manipulations. This goal is different from that of image watermarking which embeds into the image a signature surviving most manipulations. Existing methods for image authentication treat all types of manipulation equally (i.e., as unacceptable). However, some applications demand techniques that can distinguish acceptable manipulations (e.g., compression) from malicious ones. In this paper, we describe an effective technique for image authentication which can prevent malicious manipulations but allow JPEG lossy compression. The authentication signature is based on the invariance of the relationship between DCT coefficients of the same position in separate blocks of an image. This relationship will be preserved when these coefficients are quantized in a JPEG compression process. Our proposed method can distinguish malicious manipulations from JPEG lossy compression regardless of how high the compression ratio is. We also show that, in different practical cases, the design of authenticator depends on the number of recompression times and on whether the image is decoded into integral values in the pixel domain during the recompression process. Theoretical and experimental results indicate that this technique is effective for image authentication.
13476763
CPU/power-constrained mobile devices
Due to the limited processing capability, memory constraints, and the power budget of mobile clients, multimedia coders and/or decoders are often difficult to implement on wireless handheld PDAs. In this Universal Tuner project, we designed and implemented a wireless video streaming system that transcodes MPEG-1/2 videos or live TV broadcasting videos to the BW or indexed color Palm OS devices. In our system, the complexity of multimedia compression and decompression algorithms is adaptively partitioned between the encoder and decoder. A mobile client would selectively disable or reenable stages of the algorithm to adapt to the device's effective processing capability. Our variable-complexity strategy of selective disabling of modules supports graceful degradation of the complexity of multimedia coding and decoding into a mobile client's low-power mode, i.e. the clock frequency of its next-generation low power CPU has been scaled down to conserve power. We modified the structure of the standard motion-compensated DCT video codecs to implement a simplified the encoder on a PC server and the decoder on a complexity-constrained PDA viewing client.
26305379
A parallel decoding algorithm for IFS codes without transient behavior
Iterated function systems (IFSs) have received great attention in encoding and decoding fractal images. Barnsley (1988) has shown that IFSs for image compression can achieve a very high compression ratio for a single image. However, the major drawback of such a technique is the large computation load required to both encode and decode a fractal image. We provide a novel algorithm to decode IFS codes. The main features of this algorithm are that it is very suitable for parallel implementation and has no transient behavior. Also, from the decoding process of this method we can understand the encoding procedure explicitly. One example is illustrated to demonstrate the quality of its performance.
10152440
Watermarking capacity of digital images based on domain-specific masking effects
Our objective is to find a theoretical watermarking capacity bound of digital images based on domain-specific masking effects. We first show the capacity of private watermarking in which the power constraints are not uniform. Then, we apply several domain-specific Human Vision System approximation models to estimate the power constraints and then show the theoretical watermarking capacity of an image in a general noisy environment. Note that we consider all pixels, watermarks and noises to be discrete values, which occur in realistic cases.
8250531
Integrating Features, Models, and Semantics for TREC Video Retrieval
In this paper, we describe a system for automatic and interactive content-based retrieval of video that integrates features, models, and semantics. The novelty of the approach lies in the (I) semi-automatic construction of models of scenes, events, and objects from feature descriptors, and (2) integration of content-based and model-based querying in the search process. We describe several approaches for integration including iterative filtering, score aggregation, and relevance feedback searching. We describe our effort of applying the content-based retrieval system to the TREC video retrieval benchmark.
44754516
Noisy Speech Segmentation/Enhancement with Multiband Analysis and Neural Fuzzy Networks
This paper addresses the problem of speech segmentation and enhancement in the presence of noise. We first propose a new word boundary detection algorithm by using a neural fuzzy network (called ATF-based SONFIN algorithm) for identifying islands of word signals in fixed noise-level environment. We further propose a new RTF-based RSONFIN algorithm where the background noise level varies during the procedure of recording. The adaptive time-frequency (ATF) and refined time-frequency (RTF) parameters extend the TF parameter from single band to multiband spectrum analysis, and help to make the distinction of speech and noise signals clear. The ATF and RTF parameters can extract useful frequency information by adaptively choosing proper bands of the mel-scale frequency bank. Due to the self-learning ability of SONFIN and RSONFIN, the proposed algorithms avoid the need of empirically determining thresholds and ambiguous rules. The RTF-based RSONFIN algorithm can also find the variation of the background noise level and detect correct word boundaries in the condition of variable background noise level by processing the temporal relations. Our experimental results show that both in the fixed and variable noise-level environment, the algorithms that we proposed achieved higher recognition rate than several commonly used word boundary detection algorithms and reduced the recognition error rate due to endpoint detection.
1057171
ZPL's WYSIWYG performance model
ZPL is a parallel array language designed for high performance scientific and engineering computations. Unlike other parallel languages, ZPL is founded on a machine model (the CTA) that accurately abstracts contemporary MIMD parallel computers. This makes it possible to correlate ZPL programs with machine behavior. As a result, programmers can reason about how code will perform on a typical parallel machine and thereby make informed decisions between alternative programming solutions. The paper describes ZPL's performance model and its syntactic cues for conveying operation cost. The what you see is what you get (WYSIWYG) nature of ZPL operations is demonstrated on the IBM SP-2, Intel Paragon, SGI Power Challenge, and Cray T3E. Additionally, the model is used to evaluate two algorithms for matrix multiplication. Experiments show that the performance model correctly predicts the faster solution on all four platforms for a range of problem sizes.
40521773
Cycle decompositions of crowns
Abstract For an integer n ⩾3, the crown S n 0 is defined to be the graph with vertex set { x 0 , x 1 ,…, x n −1 , y 0 , y 1 ,…, y n −1 } and edge set {x i y j : 0⩽i,j⩽n−1, i≠j} . In this paper we give some sufficient conditions for the edge decomposition of the crown into isomorphic cycles.
12656146
Session-affinity aware request allocation for Web clusters
Persistent connections are increasingly being used in Web retrieval due to wide adoption of HTTP/1.1 standards. With persistent connections, the request allocation algorithm used by Web clusters is often session-grained. This article studies the caching performance of Web clusters under session-grained request allocation. It is shown that although content-based algorithms considerably improve caching performance over content-blind algorithms at the request-grained level, most performance gain is offset by the allocation dependency that arises when the requests are allocated at the session-grained level. The performance loss increases with cluster size and connection holding time. An optimization problem is then formulated for improving the caching effectiveness of session-grained allocation. The problem is proven to be NP-complete. Based on a heuristic approach, a session-affinity aware algorithm is presented that makes use of the correlation between the requests in a session. The new algorithm is shown to significantly outperform the content-based algorithm under session-grained allocation. It is also shown that optimizing session-grained allocation cannot fully compensate for the performance loss caused by allocation dependency.
18172401
SIMPLE Performance Results in ZPL
This paper presents performance results for ZPL programs running on the Kendall Square Research KSR-2 and the Intel Paragon. Because ZPL is a data parallel language based on the Phase Abstractions programming model, these results complement earlier claims that the Phase Abstractions model can lead to portability across MIMD computers. The ZPL language and selected aspects of the compilation strategy are briefly described, and performance results are compared against hand-coded programs.