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

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

doi:10.1109/tcsvt.2009.2031371

Cited by 5 publications

(4 citation statements)

References 37 publications

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“…where f and B are a focal length and a baseline between two cameras, respectively. 3D information, or depth, is utilised in many applications, including 3D reconstruction [1], view synthesis [2], object recognition [3] and multi-view video compression [4]. Traditional methods search the corresponding points between the left and the right images using block-based [4], [5] or mesh-based matching [2].…”

Section: Introductionmentioning

confidence: 99%

Fast Depth Estimation for View Synthesis

Anantrasirichai

Geravand

Braendler³

et al. 2021

2020 28th European Signal Processing Conference (EUSIPCO)

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Disparity/depth estimation from sequences of stereo images is an important element in 3D vision. Owing to occlusions, imperfect settings and homogeneous luminance, accurate estimate of depth remains a challenging problem. Targetting view synthesis, we propose a novel learning-based framework making use of dilated convolution, densely connected convolutional modules, compact decoder and skip connections. The network is shallow but dense, so it is fast and accurate. Two additional contributions -a non-linear adjustment of the depth resolution and the introduction of a projection loss, lead to reduction of estimation error by up to 20% and 25% respectively. The results show that our network outperforms state-of-the-art methods with an average improvement in accuracy of depth estimation and view synthesis by approximately 45% and 34% respectively. Where our method generates comparable quality of estimated depth, it performs 10 times faster than those methods.

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Section: Introductionmentioning

confidence: 99%

Fast Depth Estimation for View Synthesis

Anantrasirichai

Geravand

Braendler³

et al. 2021

2020 28th European Signal Processing Conference (EUSIPCO)

Self Cite

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“…For example, in immersive teleconference, there is an interaction between consumers. Participants at different geographical sites meet virtually and see each other in either free viewpoint or 3DTV style [5][6][7][8][9][10]. The immersive teleconference provides a more natural way of communications [11][12].…”

Section: Introductionmentioning

confidence: 99%

Content-Based Scalable Multi-View Video Coding Using 4D Wavelet

Lai¹,

Gao²

2017

IJHIT

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“…To get a scalable video coding, in-band prediction compensation were proposed by many researchers [10]. Nantheera Anantrasirichai applied the scheme to multi-view image coding [11]. The in-band compensation directly predicts the sub-bands of target images by using the sub-bands of reference images level by level based on the relation of subbands with different phases [10].…”

Section: Introductionmentioning

confidence: 99%

Level-by-Level Adaptive Disparity Compensated Prediction in Wavelet Domain for Stereo Image Coding

Jia

2015

Image Analysis and Processing — ICIAP 2015

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Disparity compensation prediction and transform coding are incorporated into a hybrid coding to reduce the bit-rate of multi-view images. However, aliasing and inaccurate displacement impair the performance of disparity compensation, especially in wavelet domain. In this paper, we propose a level-bylevel adaptive disparity compensated prediction scheme for scalable stereo image coding. To get spatial scalable feature, wavelet transform is first applied to the target image of a stereo image pair. A separable 2-D filter applied to the reference image is optimized for each resolution layer by minimizing the energy of the prediction high-bands of the target image. To form a multi-resolution representation, similar processes are then applied to the low-band image pairs generated by the prior resolution layer iteratively. Experimental results show that the proposed scheme can provide significant coding gain compared to other scalable coding scheme.

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

Cited by 5 publications

References 37 publications

Fast Depth Estimation for View Synthesis

Fast Depth Estimation for View Synthesis

Content-Based Scalable Multi-View Video Coding Using 4D Wavelet

Level-by-Level Adaptive Disparity Compensated Prediction in Wavelet Domain for Stereo Image Coding

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