Parameter Blending for Multi-Camera Harmonization for Automotive Surround View Systems

TL;DR

This paper introduces a harmonization algorithm for multi-camera automotive surround view systems that improves color and tone consistency across stitched images by leveraging ISP metadata, enhancing visual quality and efficiency.

Contribution

The paper presents a novel harmonization method that adjusts camera images before stitching using ISP metadata, outperforming existing global color transfer techniques.

Findings

Outperforms global color transfer in visual quality

Reduces computational cost

Enhances seamlessness of stitched images

Abstract

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.