Minervini, Massimo and Tsaftaris, Sotirios A. Classification-aware distortion metric for HEVC intra coding. In: 2015 Visual Communications and Image Processing (VCIP), December 13-16, 2015, Singapore, Singapore (2015)
Full text not available from this repository.Abstract
Increasingly many vision applications necessitate the transmission of acquired images and video to a remote location for automated processing. When the image data are consumed by analysis algorithms and possibly never seen by a human, tailoring compression to the application is beneficial from a bit rate perspective. We inject prior knowledge of the application in the encoder to make rate-distortion decisions based on an estimate of the accuracy that will be achieved when analyzing reconstructed image data. Focusing on classification (e.g., used for image segmentation), we propose a new application-aware distortion metric based on a geometric interpretation of classification error. We devise an implementation for the High Efficiency Video Coding standard, and derive optimal model parameters for the A-domain rate control algorithm by curve fitting procedures. We evaluate our approach on time-lapse sequences from plant phenotyping experiments and cell fluorescence microscopy encoded in intra-only mode, observing a reduction in segmentation error across bit rates.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Identification Number: | https://doi.org/10.1109/VCIP.2015.7457877 |
| Uncontrolled Keywords: | Bit rate;Distortion;Encoding;Image coding;Optimization;Standards |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Research Area: | Computer Science and Applications |
| Depositing User: | Caterina Tangheroni |
| Date Deposited: | 05 May 2016 13:57 |
| Last Modified: | 05 May 2016 13:57 |
| URI: | http://eprints.imtlucca.it/id/eprint/3481 |
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