| Paper ID | CI-3.3 |
| Paper Title |
MEASUREMENT CODING FRAMEWORK WITH ADJACENT PIXELS BASED MEASUREMENT MATRIX FOR COMPRESSIVELY SENSED IMAGES |
| Authors |
Rentao Wan, Fudan University, China; Jinjia Zhou, Hosei University, Japan; Bowen Huang, Fudan University, China; Hui Zeng, Zhejiang Gongshang University, China; Yibo Fan, Fudan University, China |
| Session | CI-3: Computational Photography |
| Location | Gather.Town |
| Session Time: | Thursday, 10 June, 15:30 - 16:15 |
| Presentation Time: | Thursday, 10 June, 15:30 - 16:15 |
| Presentation |
Poster
|
| Topic |
Computational Imaging: [IMT] Computational Imaging Methods and Models |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
To further compress measurements, the output of block-based compressed sensing, this work presents a measurement coding framework using measurement-domain intra prediction. In the framework, a deterministic measurement matrix based on the correlation of adjacent pixels (APMM) is proposed to embed the pixel-domain boundary information of each block to the measurement domain. By adopting APMM, the pixeldomain information can be efficiently used for measurementdomain intra prediction. To avoid the interference of pixels that are far apart and achieve a high prediction accuracy, we employ boundary measurements of neighboring blocks as reference for prediction. Finally, the residuals between measurements and predictions are processed by quantization and Huffman coding to generate a coded bit sequence for transmitting. Compared to the state-of-the-art, this work achieves a 24% decrease in bitrate and a 1.68dB increase in PSNR on average. |
