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Rate Allocation for Bayer-Pattern Image Compression with JPEG XS

: Richter, T.


Bilgin, A. ; University of Arizona; Brandeis University; Microsoft Research; IEEE Signal Processing Society:
Data Compression Conference, DCC 2019. Proceedings : Snowbird, Utah, USA, 26-29 March 2019
Piscataway, NJ: IEEE, 2019
ISBN: 978-1-72810-657-1
ISBN: 978-1-72810-658-8
Data Compression Conference (DCC) <2019, Snowbird/Utah>
Conference Paper
Fraunhofer IIS ()

Sensors in digital cameras use a technology called "Bayer Patterns'" allowing color photography with a planar arrangements of sensor elements. Alternating arrangements of red, green and blue filter masks on top of a rectangular grid of sensor elements allow capturing of color information, but also require a de-mosaicing algorithm to reconstruct a full-resolution color image from the sensor data. In high-speed applications, or applications where the system design requires low-latency, low-complexity compression, the JPEG~XS standard of the JPEG committee offers an elegant solution to compress Bayer pattern images close to the sensor, and to transmit the compressed data over a lower bandwidth connection while maintaining visually lossless quality. This paper discusses algorithms, and in particular modifications to the rate allocation of JPEG XS to enable compression of Bayer pattern sensor data. The main contribution of this work is a modified algorithm to compute band gains and band priorities that ensures PSNR-optimality of the demosaiced image rather the Bayer pattern itself.