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SPNet: a size-variant progressive network for aero-optical thermal radiation effects correction.
Opt Express ; 31(26): 43630-43646, 2023 Dec 18.
Article en En | MEDLINE | ID: mdl-38178454
ABSTRACT
When an aircraft is flying at a high speed, the airflow meets the optical cover and is compressed, resulting in aero-optical thermal radiation effects that degrade image quality. In this paper, based on the inherent characteristic that the degrade level of the thermal radiation bias field remains consistent regardless of image size, a size-variant progressive aero-optical thermal radiation effects correction network (SPNet) is proposed. First, SPNet uses two sub-networks to progressively correct degraded image, first and second sub-networks are responsible for learning coarse and accurate thermal radiation bias fields respectively. Second, we introduce the multi-scale feature upsampling module (MFUM) to leverage the multi-scale information of the features and promote inter-channel information interaction. Third, we propose an adaptive feature fusion module (AFFM) to dynamically fuse features from different scales by assigning different weights. At last, a multi-head self-attention feature extraction module (MSFEM) is proposed to extract global information feature maps. Compared with state-of-the-art thermal radiation effects correction methods, experiments on both simulated and real degraded images demonstrate the performance of our proposed method.

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: Opt Express Asunto de la revista: OFTALMOLOGIA Año: 2023 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: Opt Express Asunto de la revista: OFTALMOLOGIA Año: 2023 Tipo del documento: Article