Medical imaging in hospitals requires fast and efficient image compression to support the clinical work flow and to save costs. Least-squares autoregressive pixel prediction methods combined with arithmetic coding con...
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ISBN:
(纸本)9781479923427
Medical imaging in hospitals requires fast and efficient image compression to support the clinical work flow and to save costs. Least-squares autoregressive pixel prediction methods combined with arithmetic coding constitutes the state of the art in lossless image compression. However, a high computational complexity of both prevents the application of respective CPU implementations in practice. We present a massively parallel compression system for medical volume images which runs on graphics cards. Image blocks are processed independently by separate processing threads. After pixel prediction with specialized border treatment, prediction errors are entropy coded with an adaptive binary arithmetic coder. Both steps are designed to match particular demands of the parallel hardware architecture. Comparisons with current image and video coders show efficiency gains of 3.3-13.6% while compression times can be reduced to a few seconds.
Transform coding plays a key role in state-of-the-art video coders, such as HEVC. However, transforms used in current solutions do not cover the varieties of video coding signals. This work presents an adaptive transf...
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ISBN:
(纸本)9781479983407
Transform coding plays a key role in state-of-the-art video coders, such as HEVC. However, transforms used in current solutions do not cover the varieties of video coding signals. This work presents an adaptive transform design method that enables the use of multiple transforms in HEVC. A different transform set is learnt for each intra prediction mode, allowing the video encoder to perform better decisions regarding block sizes, prediction modes and transforms. Different systems are proposed to accommodate trade-offs between complexity and performance. Bit rate reductions in the range of 2% to 7% are reported, depending on complexity.
Current video coders exploit temporal dependencies via prediction that consists of motion-compensated pixel copying operations. Such per-pixel temporal prediction ignores important underlying spatial correlations, as ...
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ISBN:
(纸本)9781479983407
Current video coders exploit temporal dependencies via prediction that consists of motion-compensated pixel copying operations. Such per-pixel temporal prediction ignores important underlying spatial correlations, as well as considerable variations in temporal correlation across frequency components. In the transform domain, however, spatial decorrelation is first achieved, allowing for the true temporal correlation at each frequency to emerge and be properly accounted for, with particular impact at high frequencies, whose lower correlation is otherwise masked by the dominant low frequencies. This paper focuses on effective design of transform domain temporal prediction that: i) fully accounts for the effects of sub-pixel interpolation filters, and ii) circumvents the challenge of catastrophic design instability due to quantization error propagation through the prediction loop. We design predictors conditioned on frequency and sub-pixel position, employing an iterative open-loop (hence stable) design procedure that, on convergence, approximates closed-loop operation. Experimental results validate the effectiveness of both the asymptotic closed-loop design procedure and the transform-domain temporal prediction paradigm, with significant and consistent performance gains over the standard.
Medical applications like Computed Tomography (CT) or Magnetic Resonance Tomography (MRT) often require an efficient scalable representation of their huge output volumes in the further processing chain of medical rout...
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ISBN:
(纸本)9781509041183
Medical applications like Computed Tomography (CT) or Magnetic Resonance Tomography (MRT) often require an efficient scalable representation of their huge output volumes in the further processing chain of medical routine. A downscaled version of such a signal can be obtained by using image and video coders based on wavelet transforms. The visual quality of the resulting lowpass band, which shall be used as a representative, can be improved by applying motion compensation methods during the transform. This paper presents a new approach of using the distorted edge lengths of a mesh-based compensated grid instead of the approximated intensity values of the underlying frame to perform a motion compensation. We will show that an edge adaptive graph-based compensation and its usage for compensated wavelet lifting improves the visual quality of the lowpass band by approximately 2.5 dB compared to the traditional mesh-based compensation, while the additional filesize required for coding the motion information doesn't change.
To progress the compression performance of standard video coding algorithms, emerging motion compensation techniques will need to be integrated with the current standard techniques such as those used in the H.264. Hig...
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ISBN:
(纸本)9781424456536;9781424456543
To progress the compression performance of standard video coding algorithms, emerging motion compensation techniques will need to be integrated with the current standard techniques such as those used in the H.264. Higher order motion models, geometry-adaptive partitioning and motion-assisted merging are such techniques that can be considered for the next generation of video coders. In this paper, we examine how geometry information can benefit the use of elastic motion models to accomplish better prediction. Relative complexity issues are also discussed which is important in the standardization process. Experimental results suggest that geometry-adaptive block partitioning can add to the performance of elastic motion models to a certain extent, although the increased complexity is of some concern for real-time coding applications.
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