BAIFA: A Brightness Adaptive Image Fusion Algorithm for Robotic Visual Perception In robot tasks, camera is widely used for scene recognition and localization. However, it is still a challenging problem for robot vision working well in lowbrightness environments. We propose a brightness adaptive image fusion algorithm (BAIFA) which fuses one RGB image and one infrared image to improve the quality of image for robotic visual perception. A weight function is presented to calculate the image brightness weight to balance RGB and infrared images in fusion. To verify the proposed algorithm, comparisons with three image fusion algorithms are made in different brightness environments. Experimental results show that the proposed BAIFA is able to effectively preserve image contrast and target contour, which is more robust than others in various brightness environments. Furthermore, a case study shows that, visual perception is improved with our method and the fused image can also provide visual data in mobile robots.

Camera Exposure Control for Robust Robot Vision with NoiseAware Image Quality Assessment In this paper, we propose a noiseaware exposure control algorithm for robust robot vision. Our method aims to capture bestexposed images, which can boost the performance of various computer vision and robotics tasks. For this purpose, we carefully design an image quality metric that captures complementary quality attributes and ensures lightweight computation. Specifically, our metric consists of a combination of image gradient, entropy, and noise metrics. The synergy of these measures allows the preservation of sharp edges and rich texture in the image while maintaining a low noise level. Using this novel metric, we propose a realtime and fully automatic exposure and gain control technique based on the NelderMead method. To illustrate the effectiveness of our technique, a large set of experimental results demonstrates the higher qualitative and quantitative performance compared with conventional approaches.