Zhongwei Tang

TL;DR: A strategy to efficiently denoise multi-images or video by using a complex image processing chain involving accurate registration, video equalization, noise estimation and the use of state-of-the-art denoising methods that can be estimated accurately from the image burst.

TL;DR: This paper addresses the question of identifying the right camera direct or inverse distortion model, permitting a high subpixel precision to fit to real camera distortion, and concluded that, although high degree polynomials were required to reach a high precision of 1/100 pixels, such polynmials were easily estimated and produced a precise distortion modeling without overfitting.

TL;DR: A robust geometric stereorectification method by a three-step camera rotation is proposed and mathematically explained and shows that the algorithm has an accuracy comparable to the state-of-art, but finds the right minimum in cases where other methods fail, namely when the epipolar lines are far from horizontal.

TL;DR: In this article, a numerical processing chain permitting to achieve jointly the two mentioned goals: an accurate noise model for the camera, which is used crucially to obtain a state of the art multi-images denoising.

TL;DR: In this article , an innovative geometric error compensation method is proposed to the machining with non-rotary cutters based on two main points: 1) the cutter rotation angle is considered to both the modeling and compensation of the geometric errors; 2) the instantaneous ideal contact point, which is calculated according to the generation process of the worm grinding of face gears, is chosen as the reference point to the compensation algorithm rather than the cutter tip point used in the previous method.