Multi-view image coding with wavelet lifting and in-band disparity compensation

Anantrasirichai, Nantheera; Canagarajah, C N; Bull, David

doi:10.1109/icip.2005.1530321

Cited by 6 publications

(4 citation statements)

References 12 publications

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“…In experiments, the dynamic programming proposed in [13] was utilised to estimate depth maps. The volumetric compression proposed < view-2 /in [14] was employed in the pre-processing system, whilst in-band disparity compensated view filtering scheme (a) proposed in [15] was employed for data compression in the post-processing. Three multi-view test sequences: Head', Santa' and Leo2, were used for testing the proposed scheme.…”

Section: Lt 5 Experimental Resultsmentioning

confidence: 99%

Volumetric Reconstruction with Compressed Data

Anantrasirichai

Canagarajah

Redmill

et al. 2007

2007 First ACM/IEEE International Conference on Distributed Smart Cameras

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ABSTRACTvolumetric representation removes redundant data among views. For view synthesis, the volumetric representation Volumetric reconstruction is one of the 3D processing produces consistent 3D information thereby improving the technologies for multi-view systems. The existing methods accuracy of depths and view synthesis performance, whilst of volume reconstruction have been proposed by exploiting synthesising directly from depth maps estimated individually the original views with many constraints. These algorithms may cause errors due to their inconsistency. may not be suitable for the distributed camera system where In conventional image and video coding, system multiple views are transmitted via lossy networks before complexity in transmitters is much higher than in receivers. processing at the computing centre. Therefore, this paper However, many applications, e.g. sensor networks and proposes a novel volumetric reconstruction from the multi-camera systems, require the complex process to be compressed multi-view images. The algorithm starts with the done in the receivers because of the limited capacities of the depth registration, and then the initial volume is refined.transmitter [1]. The 3D processing is consequently forced to Finally the colour selection scheme provides the realistic operate in the receiver in which some details of the reference colour to the volume thereby achieving subjective quality of views are lost and may not be sufficient to extract the correct rendering views as shown in the subjective results. The 3D information. performance of the proposed scheme reconstructing with the In this paper, we present a novel volumetric compressed views may be inferior than reconstructing with reconstruction which is applicable for the distributed camera the original views up to 3 dB, but it can be superior over 3 system. We propose the reconstruction of a 3D object from a dB at low bitrate.sparse set of 2D compressed images which is originally taken from several angles with wide-baseline geometry. The Index Terms-volumetric reconstruction, multiview sparse multi-views are generally preferred in the distributed cameras in order to prevent the difficulty of synchronisation

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Section: Lt 5 Experimental Resultsmentioning

confidence: 99%

Volumetric Reconstruction with Compressed Data

Anantrasirichai

Canagarajah

Redmill

et al. 2007

2007 First ACM/IEEE International Conference on Distributed Smart Cameras

Self Cite

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“…The direct subband-to-subband prediction makes disparity estimation at coarse resolution more precise. Additionally, the proposed hybrid prediction scheme enhances the disparity estimation, since it can compensate for the effect of the occlusion [24].…”

Section: Multi-view Image Codec With In-band Disparity Compensatmentioning

confidence: 99%

In-Band Disparity Compensation for Multiview Image Compression and View Synthesis

Anantrasirichai

Canagarajah

Redmill

et al. 2010

IEEE Trans. Circuits Syst. Video Technol.

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“…The wavelet coefficients in each subband are coded using SPIHT algorithm [8] in a blockwise basis. In [9], Anantrasirichai et al achieved a spatial scalability of image views via in-band disparity estimation and compensation with the wavelet lifting scheme. The adaptive wavelet lifting framework used for disparity compensation was proposed by Lasang et al [10].…”

Section: Introductionmentioning

confidence: 99%

Rate Distortion Analysis and Bit Allocation Scheme for Wavelet Lifting-Based Multiview Image Coding

Lasang¹,

Kumwilaisak²

2009

EURASIP J. Adv. Signal Process.

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This paper studies the distortion and the model-based bit allocation scheme of wavelet lifting-based multiview image coding. Redundancies among image views are removed by disparity-compensated wavelet lifting (DCWL). The distortion prediction of the low-pass and high-pass subbands of each image view from the DCWL process is analyzed. The derived distortion is used with different rate distortion models in the bit allocation of multiview images. Rate distortion models including power model, exponential model, and the proposed combining the power and exponential models are studied. The proposed rate distortion model exploits the accuracy of both power and exponential models in a wide range of target bit rates. Then, low-pass and high-pass subbands are compressed by SPIHT (Set Partitioning in Hierarchical Trees) with a bit allocation solution. We verify the derived distortion and the bit allocation with several sets of multiview images. The results show that the bit allocation solution based on the derived distortion and our bit allocation scheme provide closer results to those of the exhaustive search method in both allocated bits and peak-signal-to-noise ratio (PSNR). It also outperforms the uniform bit allocation and uniform bit allocation with normalized energy in the order of 1.7-2 and 0.3-1.4 dB, respectively.

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Multi-view image coding with wavelet lifting and in-band disparity compensation

Cited by 6 publications

References 12 publications

Volumetric Reconstruction with Compressed Data

Volumetric Reconstruction with Compressed Data

In-Band Disparity Compensation for Multiview Image Compression and View Synthesis

Rate Distortion Analysis and Bit Allocation Scheme for Wavelet Lifting-Based Multiview Image Coding

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