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A Transmittance Optimization-based Framework for Image Dehazing on Multi-rotor Drones Imaging by Zonglin Li is a scholarly article available to read on EtoBox.

What is A Transmittance Optimization-based Framework for Image Dehazing on Multi-rotor Drones Imaging about?

The imaging quality of images collected by multi-rotor drones determines its practical application effects. However, current image enhancement dehazing methods have problems such as being affected by depth information, high computational complexity, and artefacts in the restoration results. In this paper, based on the dark channel prior model, a tolerance mechanism is introduced in the transmittance estimation part. The total variation (TV) model constrained by the l 1 -norm is used to refine the transmittance estimation. In addition, to reduce our algorithm's calculation, we use down-sampling technology to reduce the original image to obtain the transmittance part. Then we calculate the transmittance of the small resolution image. In the end, we can generate the transmittance of the original image by interpolation. The experimental data processing results verify the effectiveness of our algorithm. CCS CONCEPTS • Computing methodologies → Reconstruction.

Author

Zonglin Li

Publisher

ACM

Published

2022

Language

EN