Abstract
Multi-spectral RGB-NIR sensors have become ubiquitous in recent years. These sensors allow the visible and near-infrared spectral bands of a given scene to be captured at the same time. With such cameras, the acquired imagery has a compromised RGB color representation due to near-infrared bands (700–1100 nm) cross-talking with the visible bands (400–700 nm). This paper proposes two deep learning-based architectures to recover the full RGB color images, thus removing the NIR information from the visible bands. The proposed approaches directly restore the high-resolution RGB image by means of convolutional neural networks. They are evaluated with several outdoor images; both architectures reach a similar performance when evaluated in different scenarios and using different similarity metrics. Both of them improve the state of the art approaches.
Highlights
Color image restoration is the process applied to a given image in order to obtain color image values similar to the real ones
(ground truth). (3rd row) Results from Convolutional and Deconvolutional Neural Network (CDNet). (4th row) Results from ENDENet. (5th row) Results obtained with the Super-Resolution Convolutional Neural Network (SRCNN) ([30]). (6th row) Results obtained with ref. [21]. (7th row) Results obtained with ref
This paper proposed two variants of a deep learning framework for RGB color restoration from multi-spectral images, using images from the domain of visible and near-infrared wavelengths
Summary
Color image restoration is the process applied to a given image in order to obtain color image values similar to the real ones. Contrary to these approaches, in the current work, a RGB color restoration from a multi-spectral image (RGBN, N: NIR), based on the deep learning framework, is proposed which assumes that the sensor responses are unknown. In the current work, a RGB color restoration from a multi-spectral image (RGBN, N: NIR), based on the deep learning framework, is proposed which assumes that the sensor responses are unknown These images are acquired by an SSC which generates a single image containing all bands (RGBN: visible and near infrared wavelength spectral bands).
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