To efficiently protect the ownership of multimedia data with watermarking technology, a novel image watermarking algorithm based on discrete wavelet transform (DWT) and memetic algorithm (MA) is proposed in this paper...
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ISBN:
(纸本)9780769532585
To efficiently protect the ownership of multimedia data with watermarking technology, a novel image watermarking algorithm based on discrete wavelet transform (DWT) and memetic algorithm (MA) is proposed in this paper. The watermark is embedded to subband coefficients of subimage which is extracted from the original image with DWT, and watermark extraction is efficiently performed via MA. Experimental results show that the proposed watermarking algorithm results in almost invisible difference between the watermarked image and the original image, and is robust to common image processing operations and JPEG lossy compression.
In this paper, we report work on generalizing spatial relationships between the DCTs of any block and its sub-blocks, which paves the way for image processing in the JPEG compressed domain. The results reveal that DCT...
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In this paper, we report work on generalizing spatial relationships between the DCTs of any block and its sub-blocks, which paves the way for image processing in the JPEG compressed domain. The results reveal that DCT coefficients of any block can be directly obtained from the DCT coefficients of its sub-blocks and the inter-block relationship remains to be linear. Due to the fact that the corresponding coefficient matrix of linear combination is sparse, the computational complexity of the proposed algorithms is significantly lower than that of the existing methods.
Compressive sensing (CS) is an emerging model-based framework for signal recovery at a rate significantly below the Nyquist sampling rate. The CS theory states that a signal having a sparse representation in some base...
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ISBN:
(纸本)9781424454402
Compressive sensing (CS) is an emerging model-based framework for signal recovery at a rate significantly below the Nyquist sampling rate. The CS theory states that a signal having a sparse representation in some bases can be reconstructed from a small set of random projections. In this paper, a reconstruction method is developed based on block CS and adaptive choice of frame expansions according to spatial features of partitioned regions. Natural image is divided into different types of regions, the discrete cosine transform (DCT) is used for smooth regions, while the bi-orthogonal wavelet transform (OWT) is chosen for uneven regions. Several experiments are conducted on benchmark images to verify the efficacy of the proposed method. Experimental results show that it achieves improved quality in both subjective and objective measurement as compared with existing methods.
This paper presents an SoC platform based design for the implementation of an AAC audio decoder. We present the approach not only for the characteristics of the algorithm, but also provide the numerical decision for e...
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ISBN:
(纸本)0780388348
This paper presents an SoC platform based design for the implementation of an AAC audio decoder. We present the approach not only for the characteristics of the algorithm, but also provide the numerical decision for evaluation of the various approaches. The overall system is first analyzed and profiled with the ARM profiler. Then the decoder system is partitioned into software part and hardware part respectively based on the property of analysis. The software part is developed for the implementation of intensive decision making operations needed for audio bitstreams. The hardware part is a dedicated hardware for the regular and computation intensive operations in AAC audio decoding. The decoder system is realized on the ARM integrator platform where the hardware and software is communicated efficiently with the AMBA architecture.
Recently a terminal having the multiple interfaces for communication may further support a high data throughput and more robust connectivity. MPEG Media Transport (MMT) was standardized as a digital container standard...
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ISBN:
(纸本)9781509013265
Recently a terminal having the multiple interfaces for communication may further support a high data throughput and more robust connectivity. MPEG Media Transport (MMT) was standardized as a digital container standard by Moving Picture Expert Group(MPEG) in March 2014 for next-generation broadcasting and communication services. MMT is to allow efficient transmission and processing of the video, audio and signaling information to support the new service such as Ultra High Definition TV (UHD TV), multi-screen service, and etc. In this paper, we design an MMT based Hybrid delivery system (MHD system) to provide seamless UHD TV service using satellite broadcasting link and broadband link. Our system uses two network interfaces, one is DVB-S2 for satellite broadcasting service and the other one is Ethernet for broadband IP data service, especially we use a broadband link for providing a high connection reliability when satellite link has a problem. And we design our system to support compatibility to the MPEG2-TS based legacy satellite broadcasting system for the MMT based new services.
In an MPEG Advanced Audio Coder (AAC), for each frequency subband, the quantization parameter called scale factor controls the quantization noise and the bit rate. Tuning this coder would require a characterization of...
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In an MPEG Advanced Audio Coder (AAC), for each frequency subband, the quantization parameter called scale factor controls the quantization noise and the bit rate. Tuning this coder would require a characterization of the rate-distortion function per subband, which seems to be available only in a parametric manner. In this paper, we show that an accurate model for the quantization noise, depending on the scale factor value, can lead to a simple expression of the relation between the scale factor and the error power per subband. In other terms, we are now able to obtain an explicit writing of the distortion-rate function. In a second time, we apply these results to the coding algorithm in case of a fixed output bit rate and propose a new coding algorithm. Unlike the one described in the informative annex of the MPEG-2 standard, it makes use of a single loop and happens to be faster and more flexible towards psychoacoustic criteria.
Sparse signal approximation can be used to design efficient low bit-rate coding schemes. It heavily relies on the ability to design appropriate dictionaries and corresponding decomposition algorithms. The size of the ...
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Sparse signal approximation can be used to design efficient low bit-rate coding schemes. It heavily relies on the ability to design appropriate dictionaries and corresponding decomposition algorithms. The size of the dictionary, and therefore its resolution, is a key parameter that handles the tradeoff between sparsity and tractability. This work proposes the use of a non adaptive random sequence of subdictionaries in a greedy decomposition process, thus browsing a larger dictionary space in a probabilistic fashion with no additional projection cost nor parameter estimation. This technique leads to very sparse decompositions, at a controlled computational complexity. Experimental evaluation is provided as proof of concept for low bit rate compression of audio signals.
This paper proposes a method to enhance the quality of the decompressed JPEG images. A so-called Modified Coefficient Adjustment Block is used to record the round off situation while the DCT coefficients in a block ar...
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This paper proposes a method to enhance the quality of the decompressed JPEG images. A so-called Modified Coefficient Adjustment Block is used to record the round off situation while the DCT coefficients in a block are quantized according to a given quantization block. During decompression, the information recorded in the Modified Coefficient Adjustment Block is then used to adjust the de-quantized DCT coefficients before the Inverse DCT transformation. The experimental results show our method provides significantly better results than the method proposed by Chang et al.
This paper describes PSALM, a recently developed tool for business intelligence. The tool is based on MySQL database and web robot, both supported by routines developed in Java and PHP. The PSALM assembles patent data...
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This paper describes PSALM, a recently developed tool for business intelligence. The tool is based on MySQL database and web robot, both supported by routines developed in Java and PHP. The PSALM assembles patent data from publicly available data bases, it collects and analyses bibliographic parameters of patents but also does text mining. High-dimensional data contained in the patent documents are transformed into much lower dimensionality space (2D or 3D), clustered and visualized. The PSALM functionality and usability is demonstrated on MPEG-2 essential patents' portfolio.
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