Title: Bit-Plane Coding in Extractable Source Coding: optimality, modeling, and application to 360° data

Authors: Fangping Ye, Navid Mahmoudian Bidgoli, Elsa Dupraz, Aline Roumy, Karine Amis, Thomas Maugey

In extractable source coding, multiple correlated sources are jointly compressed but can be individually accessed in the compressed domain. Performance is measured in terms of storage and transmission rates. This problem has multiple applications in interactive video compression such as Free Viewpoint Television or navigation in 360° videos. In this paper, we analyze and improve a practical coding scheme. We consider a binarized coding scheme, which insures a low decoding complexity. First, we show that binarization does not impact the transmission rate but only slightly the storage with respect to a symbol based approach. Second, we propose a Q-ary symmetric model to represent the pairwise joint distribution of the sources instead of the widely used Laplacian model. Third, we introduce a novel pre-estimation strategy, which allows to infer the symbols of some bit planes without any additional data and therefore permits to reduce the storage and transmission rates. In the context of 360° images, the proposed scheme allows to save 14\% and 34\% bitrate in storage and transmission rates respectively.

Title: Fine granularity access in interactive compression of 360-degree images based on rate adaptive channel codes

Authors: N. Mahmoudian-Bidgoli, T. Maugey, A. Roumy

Abstract: In this paper, we propose a new interactive compression scheme for omnidirectional images. This requires two characteristics: efficient compression of data, to lower the storage cost, and random access ability to extract part of the compressed stream requested by the user (for reducing the transmission rate). For efficient compression, data needs to be predicted by a series of references that have been pre-defined and compressed. This contrasts with the spirit of random accessibility. We propose a solution for this problem based on incremental codes implemented by rate adaptive channel codes. This scheme encodes the image while adapting to any user request and leads to an efficient coding that is flexible in extracting data depending on the available information at the decoder. Therefore, only the information that is needed to be displayed at the users side is transmitted during the user’s request as if the request was already known at the encoder. The experimental results demonstrate that our coder obtains better transmission rate than the state-of-the-art tile-based methods at a small cost in storage. Moreover, the transmission rate grows gradually with the size of the request and avoids a staircase effect, which shows the perfect suitability of our coder for interactive transmission.

Title: Optimal reference selection for random access in predictive coding schemes

Authors: M. Q. Pham, A. Roumy, T. Maugey, E. Dupraz, M. Kieffer

Abstract: Data acquired over long periods of time like High Definition (HD) videos or records from a sensor over long time intervals, have to be efficiently compressed, to reduce their size. The compression has also to allow efficient access to random parts of the data upon request from the users. Efficient compression is usually achieved with prediction between data points at successive time instants. However, this creates dependencies between the compressed representations, which is contrary to the idea of random access. Prediction methods rely in particular on reference data points, used to predict other data points, and the placement of these references balances compression efficiency and random access. Existing solutions to position the references use ad hoc methods. In this paper, we study this joint problem of compression efficiency and random access. We introduce the storage cost as a measure of the compression efficiency and the transmission cost for the random access ability. We show that the reference placement problem that trades off storage with transmission cost is an integer linear programming problem, that can be solved by standard optimizer. Moreover, we show that the classical periodic placement of the references is optimal, when the encoding costs of each data point are equal and when requests of successive data points are made. In this particular case, a closed form expression of the optimal period is derived. Finally, the optimal proposed placement strategy is compared with an ad hoc method, where the references correspond to sources where the prediction does not help reducing significantly the encoding cost. The optimal proposed algorithm shows a bit saving of -20% with respect to the ad hoc method.

Title: Incremental coding for extractable compression in
the context of Massive Random Access

Autors: Thomas Maugey, Aline Roumy, Elsa Dupraz, Michel Kieffer

Abstract: in this paper, we study the problem of source coding with Massive Random Access (MRA). A set of correlated sources is encoded once for all and stored on a server while a large number of clients access various subsets of these sources. Due to the number of concurrent requests, the server is only able to extract a bitstream from the stored data: no re-encoding can be performed before the transmission of the data requested by the clients.
First, we formally define the MRA framework and propose to model the constraints on the way subsets of sources may be accessed by a navigation graph. We introduce both storage and transmission costs to characterize the performance of MRA. We then propose an Incremental coding Based Extractable Compression (IBEC) scheme. We first show that this scheme is optimal in terms of achievable storage and transmission costs. Second, we propose a practical implementation of our IBEC scheme based on rate-compatible LDPC codes. Experimental results show that our IBEC scheme can almost reach the same transmission costs as in traditional point-to-point source coding schemes, while having a reasonable overhead in terms of storage cost.

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