This paper presents a bit-depth scalable coding solution that is compatible with the scalable extension of H.264/Advanced Video coding (AVC), also referred to as scalable video coding (SVC). The proposed solution is c...
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This paper presents a bit-depth scalable coding solution that is compatible with the scalable extension of H.264/Advanced Video coding (AVC), also referred to as scalable video coding (SVC). The proposed solution is capable of providing an 8-bit AVC main profile or high-profile base layer-coded bitstream multiplexed with a higher bit-depth-enhancement layer coded bitstream generated through macroblock level inter-layer bit-depth prediction. New decoding processes for inter-layer prediction are introduced to enable bit-depth scalability. Compatibility with other types of scalability in the SVC standard-temporal, spatial, and SNR scalability-is ensured. It also supports the single-loop decoding required in the SVC specification. Furthermore, it supports adaptive inter-layer prediction to determine whether or not the inter-layer bit-depth prediction shall be invoked. This solution is implemented on the basis of the SVC reference software Joint scalable Video Model version 8.12. Experimental results are presented on 8-bit to 10-bitbit-depth scalability and also combined bit-depth and spatial scalability.
In this paper, we propose a bit-depthscalable lossless coding method for high dynamic range (HDR) images based on a reversible logarithmic mapping. HDR images are generally expressed as floating-point data, such as i...
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In this paper, we propose a bit-depthscalable lossless coding method for high dynamic range (HDR) images based on a reversible logarithmic mapping. HDR images are generally expressed as floating-point data, such as in the OpenEXR or RGBE formats. Our bit-depth scalable coding approach outputs base layer data and enhancement layer data. It can reconstruct the low dynamic range (LDR) image from the base layer data and reconstructs the HDR image by adding the enhancement layer data. Most previous two-layer methods have focused on the lossy coding of HDR images. Unfortunately, the extension of previous lossy methods to lossless coding does not significantly compress the enhancement layer data. This is because the bitdepth becomes very large, especially for HDR images in floating-point data format. To tackle this problem, we apply a reversible logarithmic mapping to the input HDR data. Moreover, we introduce a format conversion to avoid any degradation in the quality of the reconstructed LDR image. The proposed method is effective for both OpenEXR and RGBE formats. Through a series of experiments, we confirm that the proposed method decreases the volume of compressed data while maintaining the visual quality of the reconstructed LDR images.
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