We present a new, block-based image codec based on sparse representations using a learned, structured dictionary called the Iteration Tuned and Aligned Dictionary (ITAD). The question of selecting the number of atoms ...
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We present a new, block-based image codec based on sparse representations using a learned, structured dictionary called the Iteration Tuned and Aligned Dictionary (ITAD). The question of selecting the number of atoms used in the representation of each image block is addressed with a new, global (image-wide), rate-distortion-based sparsity selection criterion. We show experimentally that our codec outperforms JPEG2000 in both quantitative evaluations (by 0.9 dB to 4 dB) and qualitative evaluations.
With stereo audio steping into people's daily lives, spatial parametric technology comes to its broad prospects for development. Spatial parameteric technology is a method for stereo compression. MDCT is excluded ...
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With stereo audio steping into people's daily lives, spatial parametric technology comes to its broad prospects for development. Spatial parameteric technology is a method for stereo compression. MDCT is excluded in the current scheme for spatial cues representation,due to its lacking of phase information and energy conservation. In this paper, Construction of new spatial parameter codec framework in MDCT domain, and Optimization of calculating for the new module, to reduce computational complexity of the system. A Modified Spatial Parameter Codec Algorithm in MDCT Domain was proposed to improve it. The MDCT-MDST conversion, in matrix form, is approximating to a banded sparse matrix. To compare with the EaacPlus system, the output stereo of the new system gains a considerable subjective and objective test scores. This research make a contribution to the spatial parametric technology in MDCT domain, and provide a new train of thought to reduce complexity of EaacPlus system.
Advances in process integration, the power wall and end-user application demands have made Multi-Processor Systems on Chip (MPSoCs) a reality. In mobile embedded devices, these systems are heterogeneous in order to co...
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Advances in process integration, the power wall and end-user application demands have made Multi-Processor Systems on Chip (MPSoCs) a reality. In mobile embedded devices, these systems are heterogeneous in order to cope with stringent real time and energy constraints, which makes them difficult to program, debug and verify. Therefore, a lot of research in industry and academia has focused on providing solutions to this MPSoC programming problem. In this paper we study and extend one of such frameworks, namely, the MPSoC Application Programming Studio (MAPS) [1]. We analyze MAPS retargetability by adding a new backend for a heterogeneous MPSoC with the OSIP hardware scheduler [2]. The new backend exports high level debugging information that is included in an environment for application debugging based on virtual platforms. The extensions are demonstrated on a heterogeneous virtual platform running the JPEG application.
Image data compressed with JPEG XR when transmitted over error-prone channels is severely distorted. In fact, due to the adaptive coding strategies used by the codec, even a single bit error causes a mismatch in the a...
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Image data compressed with JPEG XR when transmitted over error-prone channels is severely distorted. In fact, due to the adaptive coding strategies used by the codec, even a single bit error causes a mismatch in the alignment of the reading position from the bitstream, leading to completely different images at the decoder side. We propose an extension to the JPEG XR algorithm, consisting in an error recovery process enabling the decoder to realign itself to the right bitstream position and to correctly decode the most part of the image. We have performed several experiments using different encoder parameter and different error probabilities while image distortion is measured by PSNR objective metric. The simplicity of the proposed algorithm adds very little computational overhead and seems very promising as confirmed by objective image quality results in experimental tests.
This paper proposes a novel recognition scheme for semantic labeling of 2D objects present in still images. The principle consists of matching unknown 2D objects with categorized 3D models in order to associate the se...
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This paper proposes a novel recognition scheme for semantic labeling of 2D objects present in still images. The principle consists of matching unknown 2D objects with categorized 3D models in order to associate the semantics of the 3D object to the image. We tested our new recognition framework by using the MPEG-7 and Princeton 3D model databases in order to label unknown images randomly selected from the web. Experiments show that such a system can achieve recognition rate up to 70.4%.
We study the impact of a novel prioritized frame dropping scheme in buffer-constrained multiprocessor system-on-chip (MPSoC) platforms. Accurate buffer dimensioning has attracted lot of research interest as large on-c...
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We study the impact of a novel prioritized frame dropping scheme in buffer-constrained multiprocessor system-on-chip (MPSoC) platforms. Accurate buffer dimensioning has attracted lot of research interest as large on-chip buffers result in increased silicon area and higher costs. Multimedia applications present the flexibility of trading off quality for buffer space without any noticeable deterioration in video quality. The frame dropping scheme is crucial here to drop frames appropriately such that the required buffer size is reduced and target quality requirement is satisfied. Towards this, we propose a simple prioritized frame dropping mechanism which reduces the required buffer space more than existing frame dropping policies. We also provide a fast iterative procedure to find the minimum buffer size for a video clip with O(log(N drop )) number of iterations, where N drop is the maximum number of frames that can be dropped for a video clip so that a prespecified quality in terms of peak signal to noise ratio (PSNR) value is satisfied.
In this paper we propose a new JPEG-based steganography technique, using eigenvalues' properties of matrices of quantized DCT coefficients. We call this new approach, Eigenvalue Steganography. Usual steganography ...
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In this paper we propose a new JPEG-based steganography technique, using eigenvalues' properties of matrices of quantized DCT coefficients. We call this new approach, Eigenvalue Steganography. Usual steganography techniques based on JPEG images, hide data by changing the least significant bit (LSB) of DCT coefficients. Eigenvalue Steganography technique hides confidential data employing the eigenvalues of quantized DCT matrices and manipulating them. This technique suggests the subdivision of quantized DCT coefficients blocks into smaller submatrices in DCT domain. Afterwards, this technique efficiently hides confidential information among DCT submatrices, by employing the proposed algorithms and manipulating the eigenvalues of these submatrices. Experiments done in this paper, depicts that the two proposed methods to implement Eigenvalue Steganography show appropriate resistance against Subtractive Pixel Adjacency Matrix (SPAM) steganalyzer. This steganalysis model doesn't have the capability of proper detection for the suggested methods.
Compared to full encryption approaches, selective encryption approaches are known to protect JPEG images from attacks with minimum overhead for Wireless Sensor Networks (WSNs). Since data resulting from DCT transform ...
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Compared to full encryption approaches, selective encryption approaches are known to protect JPEG images from attacks with minimum overhead for Wireless Sensor Networks (WSNs). Since data resulting from DCT transform is correlated with each other, however, the unencrypted data in selective encryption approaches can give attackers some hint for guessing the encrypted data. In this paper, we propose away to apply full encryption to image transmission over WSNs by offloading the computational workload of sensors to a server. Based on the experimental results, we show that the proposed approach can ensure both the higher security level and the energy-efficiency at a sensor with acceptable image quality.
The idea of multiple description video coding has been introduced to deal with the issues of bandwidth/path diversity and packet loss due to network congestion and/or error-prone channels which might cause serious qua...
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The idea of multiple description video coding has been introduced to deal with the issues of bandwidth/path diversity and packet loss due to network congestion and/or error-prone channels which might cause serious quality degradation in video applications such as multimedia streaming and video conferencing services. In this paper, two approaches to description generation are proposed to produce multiple descriptions at higher coding efficiency. One of them is motivated by the multiple description scalar quantizer to reduce the distortion and the other is the coefficient partition in transform domain in order to balance the descriptions better. An estimation mechanism is further proposed to alleviate the drifting problem due to description fluctuation by synchronizing the reference frames at the encoder and the decoder as much as possible. The experiments show that the proposed methods offer substantial improvement at the event of description loss.
This paper proposes a new image authentication scheme, which is done in the wavelet domain. A magnitude of coefficient in selected sub-bands is determined in terms of bit plane data. An image feature is generated from...
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This paper proposes a new image authentication scheme, which is done in the wavelet domain. A magnitude of coefficient in selected sub-bands is determined in terms of bit plane data. An image feature is generated from this data and then signed to be a digital signature. The Signature can be embedded into host image or separately send. The feature is only 256 bytes. With the proposed scheme, image authentication can be performed effectively.
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