| タイトル | A Stochastic Model of Block Segmentation Based on the Quadtree and the Bayes Code for It |
|---|---|
| 著者 | 中原 悠太 、松嶋 敏泰 |
| 年度 | 2019 |
| 形式 | 国際学会 |
| 分野 | 情報源符号化 |
| 掲載雑誌名 | Proceeding of 2020 Data Compression Conference (DCC2020) |
| 掲載号・ページ | pp.293--302 |
| 掲載年 | 2020 |
| 掲載月 | 3 |
| アブスト （日本語） |
2020 Data Compression Conference (DCC) 2020年3月24日～27日 オンライン開催 査読有 DOI: 10.1109/DCC47342.2020.00037 https://ieeexplore.ieee.org/document/9105877 |
| アブスト （英語） |
In this paper, we propose a novel stochastic model based on the quadtree, so that our model effectively represents the variable block size segmentation of images. Then, we construct the Bayes code for the proposed stochastic model. In general, the computational cost to calculate the posterior distribution required in the Bayes code increases exponentially with respect to the data size. However, we introduce an efficient algorithm to calculate it in the polynomial order of the data size without loss of the optimality. Some experiments are performed to confirm the flexibility of the proposed stochastic model and the efficiency of the introduced algorithm. |
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