Parameter Blending for Multi-Camera Harmonization for Automotive Surround View Systems
This work addresses visual quality issues in automotive surround view systems, but it is incremental as it builds on existing harmonization techniques.
The paper tackles the problem of color and brightness discontinuities in multi-camera surround view systems by proposing a harmonization algorithm that adjusts color and tone before stitching, resulting in smoother transitions and outperforming global color transfer in visual quality and computational cost.
In a surround view system, the image color and tone captured by multiple cameras can be different due to cameras applying auto white balance (AWB), global tone mapping (GTM) individually for each camera. The color and brightness along stitched seam location may look discontinuous among multiple cameras which impacts overall stitched image visual quality. To improve the color transition between adjacent cameras in stitching algorithm, we propose harmonization algorithm which applies before stitching to adjust multiple cameras' color and tone so that stitched image has smoother color and tone transition between adjacent cameras. Our proposed harmonization algorithm consists of AWB harmonization and GTM harmonization leveraging Image Signal Processor (ISP)'s AWB and GTM metadata statistics. Experiment result shows that our proposed algorithm outperforms global color transfer method in both visual quality and computational cost.