Compression is an important issue in digital applications as it can reduce the storage
size and minimize the bandwith usage for file transfer over networks. In this
document, two topics about compression is discussed. The first topic presents a
novel block-based image coding algorithm which integrates tree-structured multitree
dictionary and perceptual-based rate distortion optimization scheme. While
multitree dictionary is employed to support a very large number of different tilings,
perceptual-based rate distortion optimization utilizes the SSIM metric, instead of
popular MSE metric, to allocate bit rate according to human visual system. Experimental
results show that our proposed method outperforms many existing techniques
in both subjective and objective image quality measures. The second topic
presents two novel end-to-end stereo video compression pipelines consisting of
single-sensor digital camera pairs, the legacy consumer-grade video decoders,
and anaglyph displays. As 3D videos contain a large amount of data, efficient
compression methods to distribute streams over the current communication infrastructure
are highly required. We proposed two methods to transmit a single
encoded stream containing only required data to create anaglyph video from
single-sensor camera pairs. The experimental results demonstrate the superior
performance of our proposed methods over the traditional one by achieving up to
4.66 dB improvement in terms of Composite PSNR.

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