Multiview video compression with 1-D transforms

Karasoy, Burcu
Kamışlı, Fatih
Many alternative transforms have been developed recently for improved compression of images, intra prediction residuals or motion-compensated prediction residuals. In this paper, we propose alternative transforms for multiview video coding. We analyze the spatial characteristics of disparity-compensated prediction residuals, and the analysis results show that many regions have 1-D signal characteristics, similar to previous findings for motion-compensated prediction residuals. Signals with such characteristics can be transformed more efficiently with transforms adapted to these characteristics and we propose to use 1-D transforms in the compression of disparity-compensated prediction residuals in multiview video coding. To show the compression gains achievable from using these transforms, we modify the reference software (JMVC) of the multiview video coding amendment to H.264/AVC so that each residual block can be transformed either with a 1-D transform or with the conventional 2-D Discrete Cosine Transform. Experimental results show that coding gains ranging from about 1-15% of Bjontegaard-Delta bitrate savings can be achieved.


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Multiview video compression with 1-D transforms
Karasoy, Burcu; Kamışlı, Fatih; Department of Electrical and Electronics Engineering (2013)
In previous research, it has been shown that motion compensated prediction residuals can have 1-D structures in many regions and that 1-D directional DCTs can compress such regions more e ciently than the conventional 2-D DCT. In this thesis, we analyze the spatial characteristics of the disparity compensated prediction residuals and the analysis results show that, similar to motion compensated prediction residuals, many regions of disparity compensated prediction residuals also have 1-D structures. Thus, w...
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Kayaalp, Işıl Burcun; Akar, Gözde; Department of Electrical and Electronics Engineering (2003)
In this thesis, a mixed type video segmentation algorithm is implemented to find the scene cuts in MPEG compressed video data. The main aim is to have a computationally efficient algorithm for real time applications. Due to this reason partial decoding of the bitstream is used in segmentation. As a result of partial decoding, features such as bitrate, motion vector type, and DC images are implemented to find both continuous and discontinuous scene cuts on a MPEG-2 coded general TV broadcast data. The result...
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The well-known low-complexity JPEG and the newer JPEG-XR systems are based on block-based transform and simple transform-domain coefficient prediction algorithms. Higher complexity image compression algorithms, obtainable from intra-frame coding tools of video coders H.264 or HEVC, are based on multiple block-based spatial-domain prediction modes and transforms. This paper explores an alternative low-complexity image compression approach based on a single spatial-domain prediction mode and transform, which ...
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Yesilyurt, Aziz Berkay; Kamışlı, Fatih (2021-01-24)
The use of neural networks in image compression enables transforms and probability models for entropy coding which can process images based on much more complex models than the simple Gauss-Markov models in traditional compression methods. All at the expense of higher computational complexity. In the neural-network based image compression literature, various methods to model the dependencies in the transform domain/latent space are proposed. This work uses an alternative method to exploit the dependencies o...
Citation Formats
B. Karasoy and F. Kamışlı, “Multiview video compression with 1-D transforms,” SIGNAL PROCESSING-IMAGE COMMUNICATION, pp. 14–28, 2015, Accessed: 00, 2020. [Online]. Available: