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Graph-based models have recently attracted attention for their potential to enhance transform coding image compression thanks to their capability to efficiently represent discontinuities. Graph transform gets closer to the optimal KLT by using weights that represent inter-pixel correlations but the extra cost to provide such weights can overwhelm the gain, especially in the case of natural images...
A Hyperspectral (HS) image provides observational powers beyond human vision capability but represents more than 100 times data compared to a traditional image. To transmit and store the huge volume of an HS image, we argue that a fundamental shift is required from the existing "original pixel intensity"-based coding approaches using traditional image coders (e.g. JPEG) to the "residual"...
Depth maps are becoming increasingly important in the context of emerging video coding and processing applications. Depth images represent the scene surface and are characterized by areas of smoothly varying grey levels separated by sharp edges at the position of object boundaries. To enable high quality view rendering at the receiver side, preservation of these characteristics is important. Lossless...
The statistical model of the bits to be encoded is crucial for the coding performance of distributed video coding (DVC). In this paper, a bit-level context-adaptive correlation model is proposed to exploit high-order statistical correlation for better channel coding performance, which consequently improves the video coding efficiency. In the proposed scheme, the wavelet domain DVC is considered and...
In this paper, we propose an explicit signaling of RDPCM scheme for a lossy intra-coded block, and achieve a significant coding gain over the HEVC Range Extension reference software in the screen contents coding. We define three RDPCM modes, and transmit the side information so that the best RDPCM mode can be applied to residual signals after all available angular directional predictions. Contexts...
The application of machine learning algorithms in wireless communications has attracted increasing attention due to the promising performance gains recently achieved. Static classification algorithms have been successfully applied to training protocols that adapt transmission parameters according to context information. However, in reality, there are many time-varying reasons for fading channel quality...
The recentH.264/AVCvideo coding standard provides a higher coding efficiency than previous standards. H.264/AVCachieves a bit rate saving of more than 50 % with many new technologies, but it shows very heavy computational complexity. In this paper, a fast mode decision scheme for inter-frame coding is proposed to reduce the computational complexity for H.264/AVC video encoding system. To reduce the...
In this paper, a multiband loss less compression system exploiting inter-band data correlation is presented. We develop an adaptive prediction scheme that can dynamically switch among smooth, intra and intra-band prediction modes subject to the data correlation. Specifically, we use context information to determine the inter-band correlation between neighboring bands, and then borrow the wisdom of...
In order to address the problem of failure detection in the robotics domain, we present in this contribution a so-called self-awareness model, based on the system's internal data exchange and the inherent dynamics of inter-component communication. The model is strongly data driven and provides an anomaly detector for robotics systems both applicable in-situ at runtime as well as a-posteriori in post-mortem...
A key indicator of problem difficulty in evolutionary computation problems is the landscape's locality, that is whether the genotype-phenotype mapping preserves neighbourhood. In genetic programming the genotype and phenotype are not distinct, but the locality of the genotype-fitness mapping is of interest. In this paper we extend the original standard quantitative definition of locality to cover...
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