TY  - CONF
Y1  - 2015/12//
A1  - Minervini, Massimo
A1  - Tsaftaris, Sotirios A.
T2  - 2015 Visual Communications and Image Processing (VCIP)
PB  - IEEE
UR  - http://dx.doi.org/10.1109/VCIP.2015.7457877
KW  - Bit rate;Distortion;Encoding;Image coding;Optimization;Standards
N2  - 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.
AV  - none
TI  - Classification-aware distortion metric for HEVC intra coding
ID  - eprints3481
M2  - Singapore, Singapore
ER  -