THESIS
2017
xvii, 102 pages : illustrations ; 30 cm
Abstract
Efficient video / image coding techniques are desired for the dramatically
growing demand of storage and transmission of visual information. The widely
used coding standards, e.g., H.264 and HEVC, are all based on a hybrid video
coding framework which consists of a predicting process followed by transform
coding and entropy coding. Looking into the results of encoding one image, the
discontinuous regions, i.e., regions containing edges / contours, consume most of
the coding bits because of the inaccurate prediction of the discontinuities. Due
to the arbitrariness of the contours in the image, it is impractical to accurately
predict them using a model with manageable complexity. Instead of using an
integrated predicting technique to encode both the discontinuous regions and the...[
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Efficient video / image coding techniques are desired for the dramatically
growing demand of storage and transmission of visual information. The widely
used coding standards, e.g., H.264 and HEVC, are all based on a hybrid video
coding framework which consists of a predicting process followed by transform
coding and entropy coding. Looking into the results of encoding one image, the
discontinuous regions, i.e., regions containing edges / contours, consume most of
the coding bits because of the inaccurate prediction of the discontinuities. Due
to the arbitrariness of the contours in the image, it is impractical to accurately
predict them using a model with manageable complexity. Instead of using an
integrated predicting technique to encode both the discontinuous regions and the
remaining regions as in a hybrid video coding framework, an alternative way
is to perform a separate process to the discontinuities in the image. Separate
discontinuity handling provides more freedom to design an algorithm for efficient
encoding of the discontinuous regions.
In this thesis, we focus on handling the discontinuities of the video / image in
two directions in order to improve the overall coding efficiency. We first discuss
a contour assisted coding framework which pre-encodes the discontinuities before
feeding the input image into a conventional encoder, and propose efficient algorithms
to encode the discontinuities. Then we propose a new approach, adaptive
coding order, for a hybrid video coding framework to reduce the discontinuities.
For a contour assisted coding framework, the object contours / edges (discontinuities)
are first extracted from the input frame as side information (SI), then
the input frame is encoded by utilizing SI. One key problem is how to efficiently compress SI, i.e., the contours. For the direction of contour assisted coding, we
focus on the problem of lossless and lossy compression of detected contours in the
image. Specifically, to encode the symbol sequence contour using arithmetic coding,
we compute an optimal variable-length context tree (VCT) via a maximum a
posterior (MAP) formulation to estimate the symbols' conditional probabilities.
MAP can avoid overfitting given a small training set of past symbol sequences,
using a geometric prior stating that image contours are more often straight than
curvy. For the lossy case, we design fast dynamic programming (DP) algorithms
that optimally trade off the coding rate of an approximated contour given a VCT
with two notions of distortion. The proposed algorithms are integrated in most
recent contour assisted coding framework based coders and applied to three applications.
Experimental results show that the proposed contour coding algorithms
significantly improve the overall coding performance for different applications. To
deal with the problem of compressing noised contours, we further propose a joint
contour denoising / compression algorithm based on a burst error model. We
prove both in theory and in experiments our proposed joint scheme outperforms
the competing separate schemes which first do denoising then compression.
For the direction of adaptive coding order, the order of processing the basic coding unit-a block of pixels-in hybrid video coding is adaptively adjusted
based on the edge direction rather than pre-determined in a fixed manner. Adaptively
adjusting the processing order can reduce the discontinuities in the image
by avoiding crossing the edges when performing prediction. Specifically, determining
the block coding order is formulated as a travelling salesman problem that
is solved using the DP algorithm. Experimental results show that the proposed
algorithm outperforms the state-of-the-art HEVC, which is mainly due to more
efficient coding of the discontinuous regions.
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