Correction of images projected on non-white surfaces based on deep neural network

Zewei Wang; Jingjing Zhang; Xingzhuo Du; Sihua Cao; Wenxuan Wei

doi:10.1117/12.2644283

12 October 2022 Correction of images projected on non-white surfaces based on deep neural network

Zewei Wang, Jingjing Zhang, Xingzhuo Du, Sihua Cao, Wenxuan Wei

Proceedings Volume 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022); 123423H (2022) https://doi.org/10.1117/12.2644283
Event: Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 2022, Wuhan, China

Abstract

When projecting onto a non-white surface, the projected image is distorted or color mixing by complex luminance and chrominance information, which makes the projection result different from the visual perception of the human eye. The purpose of projection image correction is to remove these effects, and traditional solutions usually estimate parameters from the collected projection samples, compute an inverse model of the projection imaging process, and try to fit a correction function. In this paper, a deep neural network-based projection image correction network (PICN) is designed to implicitly learn complex correction functions. PICN consists of a U-shaped backbone network, a convolutional neural network that extracts projected surface features, and a perceptual loss network that optimizes the correction results. Such a structure can not only extract the deep features and surface interference features of the projected image, but also make the corrected projected image more in line with human visual perception. In addition, we built a projector-camera system under the condition of a fixed global illumination environment for verification experiment, and proved the effectiveness of the proposed method by calculating the evaluation metrics of projected images before and after correction.

Citation Download Citation

Zewei Wang, Jingjing Zhang, Xingzhuo Du, Sihua Cao, and Wenxuan Wei "Correction of images projected on non-white surfaces based on deep neural network", Proc. SPIE 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 123423H (12 October 2022); https://doi.org/10.1117/12.2644283

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