RGB-thermal based denosing methods: a review of deep learning based image denosing algorithm and application

Recently, vision-based detection techonology has been developed fast and general pupose object detection algorithm has been applied in various scene. VD can be categorized into two major categories, single-modal, single RGB or single thermal, and bimodal, according to the modal type used. Generally, the first stage of image processing in VD is denoising, removing the redundancy information and promising the post processing task. Thus, this paper will give a review on RGB thermal deep learning based image denoising methods, investigating the RGB-thermal based denoising procedure, methods, benchmark and performance. After the introduction of denoising models, main results on public RGB and thermal datasets are presented and analyzed, and conclusion of objective comparison in practical effect will be proposed. This review can serve as a reference for researchers in RGB-infrared denoising, image restoration, and related fields.