  Conventional image signal processing (ISP) frameworks are designed to
reconstruct an RGB image from a single raw measurement. As multi-camera systems
become increasingly popular these days, it is worth exploring improvements in
ISP frameworks by incorporating raw measurements from multiple cameras. This
manuscript is an intermediate progress report of a new ISP framework that is
under development, StereoISP. It employs raw measurements from a stereo camera
pair to generate a demosaicked, denoised RGB image by utilizing disparity
estimated between the two views. We investigate StereoISP by testing the
performance on raw image pairs synthesized from stereo datasets. Our
preliminary results show an improvement in the PSNR of the reconstructed RGB
image by at least 2dB on KITTI 2015 and drivingStereo datasets using ground
truth sparse disparity maps.
