DCCF: Deep Comprehensible Color Filter Learning Framework for High-Resolution Image Harmonization

Image color harmonization algorithm aims to automatically match the color distribution of foreground and background images captured in different conditions. Previous deep learning based models neglect two issues that are critical for practical applications, namely high resolution (HR) image processing and model comprehensibility. In this paper, we propose a novel Deep Comprehensible Color Filter (DCCF) learning framework for high-resolution image harmonization. Specifically, DCCF first downsamples the original input image to its low-resolution (LR) counter-part, then learns four human comprehensible neural filters (i.e. hue, saturation, value and attentive rendering filters) in an end-to-end manner, finally applies these filters to the original input image to get the harmonized result. Benefiting from the comprehensible neural filters, we could provide a simple yet efficient handler for users to cooperate with deep model to get the desired results with very little effort when necessary. Extensive experiments demonstrate the effectiveness of DCCF learning framework and it outperforms state-of-the-art post-processing method on iHarmony4 dataset on images' full-resolutions by achieving 7.63% and 1.69% relative improvements on MSE and PSNR respectively.Comment: ECCV 2022 (Oral

Novel laser triangulation measurement method for screw rotor profile under multi-factor constraints

Abstract(#br)In order to achieve optimal control of the screw rotor process, a novel measurement method using laser triangulation under multi-factor constraints was introduced to achieve online measurement of the screw rotor profile. This method involved the integration of a 4-axis motion system, which is used to adjust the laser probe, with a laser displacement sensor (LDS), which is used to measure the screw rotor profile. Firstly, the effect of laser beam positioning on measurement accuracy was analyzed experimentally in conjunction with an improved LDS error compensation model. Then, according to the characteristics of rotor profiles, a laser-measurement trajectory planning algorithm for the rotor profile under multi-factor constraints was developed. Finally, the comparison study between the traditional contact measurement (P65) and the proposed measurement demonstrates that the proposed method has not only kept the advantages of traditional contact measurement, but also shown good performances and high measuring precision