Optimization of the Rate-Distortion Compromise for Stereoscopic Image Coding using Joint Entropy-Distortion Metric

Abstract : During the last decades, a wide range of applications using stereoscopic technology has emerged still offering an increased immersion to the users such as video games with autostereoscopic displays, 3D-TV or stereovisio-conferencing. The raise of these applications requires fast processing and efficient compression techniques. In particular, stereoscopic images require twice the amount of information needed to transmit or store them in comparison with 2D images as they are composed of two views of the same scene. The contributions of our work are in the field of stereoscopic image compression and more precisely, we get interested in the improvement of the disparity map estimation. Generally, disparities are selected by minimizing a distortion metric which is sometimes subjected to a smoothness constraint, assuming that a smooth disparity map needs a smaller bitrate to be encoded. But a smoother disparity map does not always reduce significantly the bitrate needed to encode it but can increase the distortion of the predicted view. Therefore, the first algorithm we have proposed minimizes a joint entropy-distortion metric to select the disparities. At each step of the algorithm, the bitrate of the final disparity map is estimated and included in the metric to minimize. Moreover, this algorithm relies on a tree where a fixed number of paths are extended at each depth of the tree, ensuring good rate-distortion performance. In the second part of the work, we have proposed a sub-optimal solution with a smaller computational complexity by considering an initial solution -the one minimizing the distortion of the predicted view- which is successively modified as long as an improvement is observed in terms of rate-distortion. Then, we have studied how to take advantages of large search areas in which the disparities are selected as one can easily supposed that enlarging the search area will increase the distortion performance as there will be more choices of disparities. In the other hand, the larger is the range of the selected disparities, the higher is supposed to be the cost of the disparity map in terms of bitrate. We have proposed two approaches allowing to take advantage of a large search area by selecting only sets of disparities belonging to it enabling to achieve a given bitrate while minimizing the distortion of the predicted image. The last part of the work concerns variable block sizes which undeniably allows to improve the bitrate-distortion performance as the block size suits to the image features. We have thus proposed a novel algorithm which jointly estimates and optimizes the disparity and the block length maps.
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Aysha-Khatoon Kadaikar. Optimization of the Rate-Distortion Compromise for Stereoscopic Image Coding using Joint Entropy-Distortion Metric. Signal and Image Processing. Université Sorbonne Paris Cité, 2017. English. ⟨NNT : 2017USPCD083⟩. ⟨tel-02381896⟩

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