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StereoISP: Rethinking Image Signal Processing for Dual Camera Systems

arXiv 2211.07390 ↗First posted 11 Nov 2022eess.IV cs.CV cs.LGcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 17 of its 27 references that are in the map. First posted on arXiv 11 Nov 2022.

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References · 17

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5 more
  1. 2015Stereo Matching by Training a Convolutional Neural Network to Compare Image Patchescited by 151
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  5. 2022What Does a One-Bit Quanta Image Sensor Offer?cited by 11

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