Abstract
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-by-level 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.
This work was supported by the Chinese Natural Science Foundation (61201452).
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Li, S., Jia, L. (2015). Level-by-Level Adaptive Disparity Compensated Prediction in Wavelet Domain for Stereo Image Coding. In: Murino, V., Puppo, E. (eds) Image Analysis and Processing — ICIAP 2015. ICIAP 2015. Lecture Notes in Computer Science(), vol 9280. Springer, Cham. https://doi.org/10.1007/978-3-319-23234-8_40
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