Frame loss error concealment for spatial scalability using hallucination

Ma, Qirong; Wu, Feng; Lou, Jian; Sun, Ming–Ting

doi:10.1109/packet.2009.5152146

Cited by 2 publications

(1 citation statement)

References 17 publications

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“…A more complex method was published recently using the information from the upscaled base layer to replace the erroneous areas in the enhancement layer, based on a technique called frame-hallucination. 13 This technique involves a training process and requires a set of available images in order to choose the best image to use for concealment. It shows interesting results when compared to the simple method based on the reconstruction of the base layer, at the price of a relatively high computational complexity.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of MPEG4-SVC for QoE protection in the context of transmission errors

et al. 2010

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Scalable Video Coding (SVC) provides a way to encapsulate several video layers with increasing quality and resolution in a single bitstream. Thus it is particularly adapted to address heterogeneous networks and a wide variety of decoding devices. In this paper, we evaluate the interest of SVC in a different context, which is error concealment after transmission on networks subject to packet loss. The encoded scalable video streams contain two layers with different spatial and temporal resolutions designed for mobile video communications with medium size and average to low bitrates. The main idea is to use the base layer to conceal errors in the higher layers if they are corrupted or lost. The base layer is first upscaled either spatially or temporally to reach the same resolution as the layer to conceal. Two error-concealment techniques using the base layer are then proposed for the MPEG-4 SVC standard, involving frame-level concealment and pixel-level concealment. These techniques are compared to the upscaled base layer as well as to a classical single-layer MPEG-4 AVC/H.264 error-concealment technique. The comparison is carried out through a subjective experiment, in order to evaluate the Quality-of-Experience of the proposed techniques. We study several scenarios involving various bitrates and resolutions for the base layer of the SVC streams. The results show that SVC-based error concealment can provide significantly higher visual quality than single-layer-based techniques. Moreover, we demonstrate that the resolution and bitrate of the base layer have a strong impact on the perceived quality of the concealment.

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Section: Introductionmentioning

confidence: 99%

Evaluation of MPEG4-SVC for QoE protection in the context of transmission errors

et al. 2010

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Subjective evaluations of example-based, total variation, and joint regularization for image processing

2012

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We report on subjective experiments comparing example-based regularization, total variation regularization, and the joint use of both regularizers. We focus on the noisy deblurring problem, which generalizes image superresolution and denoising. Controlled subjective experiments suggest that joint example-based regularization and total variation regularization can provide subjective gains over total regularization alone, particularly when the example images contain similar structural elements as the test image. We also investigate whether the regularization parameters can be trained by cross-validation, and we compare the reconstructions using crossvalidation judgments made by humans or by fully automatic image quality metrics. Experiments showed that of five image quality metrics tested, the structural similarity index (SSIM) correlates best with human judgement of image quality, and can be profitably used to cross-validate regularization parameters. However, there is a significant quality gap between images restored using human or automatic parameter cross-validation.

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Frame loss error concealment for spatial scalability using hallucination

Cited by 2 publications

References 17 publications

Evaluation of MPEG4-SVC for QoE protection in the context of transmission errors

Evaluation of MPEG4-SVC for QoE protection in the context of transmission errors

Subjective evaluations of example-based, total variation, and joint regularization for image processing

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