Lossless White Balance For Improved Lossless CFA Image and Video Compression
This work addresses a domain-specific issue for camera sensor data compression, offering an incremental improvement over existing techniques.
The paper tackles the problem of lossless compression of raw sensor data from color filter array cameras by proposing a lifting-based lossless white balance algorithm as a pre-processing step, which reduces the spatial bandwidth of chrominance signals and improves coding efficiency.
Color filter array is spatial multiplexing of pixel-sized filters placed over pixel detectors in camera sensors. The state-of-the-art lossless coding techniques of raw sensor data captured by such sensors leverage spatial or cross-color correlation using lifting schemes. In this paper, we propose a lifting-based lossless white balance algorithm. When applied to the raw sensor data, the spatial bandwidth of the implied chrominance signals decreases. We propose to use this white balance as a pre-processing step to lossless CFA subsampled image/video compression, improving the overall coding efficiency of the raw sensor data.