In 3D video systems with Multiview Video plus Depth (MVD) representation, intermediate views can be rendered from transmitted texture views and corresponding depth maps by techniques such as Depth Image Based Rendering (DIBR). Recent standardization activities in MPEG include the development for such MVD based 3DV codecs. One codec which is H.264/AVC based is called 3DV-ATM. Because of compression, reconstructed depth maps often have certain distortions, such as blurry depth edges, which can result in noticeable artifacts in the rendered views. In this paper, a method of adaptive depth edge sharpening is proposed for 3D video coding, based on the 3DV-ATM. The proposed adaptive depth edge filtering and smoothing along depth edge techniques adaptively sharpen blurry edges of the reconstructed depth frames caused by compression. Compared to the anchor software 3DV-ATM, the proposed method achieves about 7.2% bitrate reduction on average for the rendered view PSNRs versus overall bitrates with comparable runtime complexity.

We propose the use of large tree-structured dictionaries of tilings for video compression. Our first contribution is the construction of a rate-distortion cost function that admits fast search algorithms to select the optimal tiling for the motion compensation stage of a video coder. The computation of the cost is enabled through novel algorithms to approximate the bit rate and the distortion. Our second contribution is an efficient arithmetic coding algorithm to encode the selected tree-structured tiling. We illustrate the effectiveness of our approach by showing that a H.264/AVC-like video coder utilizing one of the proposed tiling selection methods results in up to 16% savings in bit rate for several standard video sequences as compared to H.264/AVC. This is accomplished with only a modest increase in the computation time at the encoder.

Existing 3D video solutions take advantages of the 2D video infrastructure, by coding two views of the stereoscopic video content in a frame-compatible manner, such as side-by-side or top-bottom. Content providers and service providers are using the existing 2D video authorizing tools and delivery infrastructure to enhance the 2D video experience into 3D with relatively small additional cost. However, such a frame-compatible solution typically sacrifices the quality of each view, by providing a half-resolution representation. In the future, it is expected that more and more devices are capable of rendering full-resolution 1080p stereoscopic video content. Co-existing of services based on half-resolution stereoscopic video, full-resolution stereoscopic video, as well as full-resolution 2D video is expected in the marketplace. In this paper, a scalable codec is proposed to support the decoding and rendering of frame-compatible stereo, full-resolution 2D and full-resolution stereo video representations. Compared to codecs providing similar functionalities, significant coding gain can be achieved.

We present in this paper the rate distortion performance analysis of the pyramid motion compensation for video spatial scalability. Theoretical performance function is derived in closed form based on quantization noise modeling. Evaluation of the rate distortion performance functions shows that, compared to intra-layer motion-compensated prediction coding the enhancement layer, pyramid method is expected to achieve more efficient compression if the base layer is encoded at a sufficient high quality, i.e., the encoded rate is high enough.

We present in this letter the rate distortion (RD) performance analysis of the inter-layer subband and pyramid motion compensation techniques for spatially scalable video coding. Theoretical performance functions are derived based on RD theory and quantization noise modeling. We assume the base layer is encoded by a non-scalable coder. The coding efficiency of the enhancement (enh.) layer, measured by the signal-to-noise ratio, is determined by the input video power spectral density, the motion estimation error distribution, and the base layer encoder rate. Numerical evaluations of the performance functions show that, compared to independent motion-compensated prediction encoding of the enh. layer, the inter-layer pyramid and subband methods are expected to be more efficient if the base layer is encoded at a sufficiently high quality or the motion estimation accuracy is relatively low in the enh. layer. Results from real video data encoding show that the presented theoretical analysis can be very useful to understand the efficiencies of these spatial scalability techniques.

In this paper, we derive the rate distortion lower bounds of spatially scalable video coding techniques. The methods we evaluate are subband and pyramid motion compensation where temporal redundancies in the same spatial layer as well as interlayer spatial redundancies are exploited in the enhancement layer encoding. The rate distortion bounds are derived from rate distortion theory for stationary Gaussian signals where mean square error is used as the distortion criteria. Assuming that the base layer is encoded by a non-scalable video coder, we derive the rate distortion functions for the enhancement layer, which depend on the power spectral density of the input signal, the motion prediction error probability density function and the base layer encoding performance. We will show that pyramid and subband methods are expected to outperform independently encoding the enhancement layer using motion-compensated prediction, in terms of rate distortion efficiency, when the base layer is encoded at a relatively higher quality or less accurate displacement estimation happens in the enhancement layer.

In this paper, we derive the rate distortion performance lower bound of the subband motion compensation technique which exploits both the inter-layer spatial and intra-layer temporal redundancies for video spatial scalability. The lower bound is derived by rate distortion theory for stationary Gaussian signals where mean square error (MSE) is used as the distortion criteria. Assuming that the base layer is encoded by an optimal non-scalable video coder, the rate distortion function derived for the enhancement layer depends on only the power spectral density (PSD) of the input signal, the motion prediction error probability density function (p.d.f.) and the base layer encoding parameter. Our evaluations will show that, if base layer is encoded at a relatively high quality, subband method is expected to outperform simulcast, where spatial layers are encoded independently, in terms of rate distortion efficiency.

This paper presents an adaptive motion compensation technique for encoding the enhancement layers in spatially scalable video coding. Based on the base layer reconstructed quantized prediction error, quantization parameters and motion vectors of both the base and enhancement layers, the proposed approach automatically selects either the inter-layer subband motion compensation, or encoding the enhancement layer without using any information from the base layer, which we call independent encoding. Compared to the SVC spatial scalability, the proposed adaptive method achieves an improvement up to about 0.6 dB with about 33% encoder computational complexity reduction.

In this paper, an efficient inter-layer motion-compensation technique is proposed for enhancement layer in spatially scalable video coding. The proposed approach exploits the prediction residue correlation between consecutive spatial layers. In enhancement-layer motion compensation, it selects the method with the lowest rate-distortion (RD) cost from three schemes: pyramid motion compensation, subband motion compensation, and encoding the enhancement layer with no base-layer information. To reduce the block artifacts of the enhancement-layer prediction used in the subband method, extended edge prediction is introduced in the proposed approach. Compared with the current scalable H.264/AVC extension (SVC) motion-compensation scheme, our experimental results show that the proposed method exploits the redundancy between the base layer and the enhancement layer more efficiently and hence improves the coding performance. It achieves an improvement up to about 1dB in the enhancement-layer encoding for different coding parameters and video sequences.

This paper describes an efficient inter-layer motion compensation approach for enhancement layer prediction in spatially scalable video coding. The proposed approach provides improved performance compared to the current motion compensation scheme in the SVC standard. The improvement in performance is achieved by adding a new mode for enhancement layer motion compensation. Our experimental results show that the proposed method achieves an improvement up to about 1 dB in a two-layer spatially scalable framework compared to current SVC enhancement layer prediction.

In this paper, a new enhancement layer motion compensation technique referred to as subband motion compensation is proposed for spatially scalable video coding. This approach is proposed as an alternative to a technique which we call pyramid motion compensation in this paper and which is referred to as inter-layer residual prediction in the H.264/MPEG4-AVC scalable extension, Scalable Video Coding (SVC) standard. The main difference between these two techniques lies in the way they use the base layer information to encode the enhancement layer. Experimental results comparing the two approaches show that for enhancement layer encoding, pyramid method is better when the corresponding base layer is encoded with a lower bitrate while subband method outperforms pyramid method when the base layer has a higher bitrate. This motivates future proposed work to adaptively choose between these two methods at the macroblock level or even at the transform coefficient level for spatially scalable video coding.