Visual enhancement of old documents with hyperspectral imaging

Abstract

Hyperspectral imaging (HSI) of historical documents is becoming more common at national libraries and archives. HSI is useful for many tasks related to document conservation and management as it provides detailed quantitative measurements of the spectral reflectance of the document that is not limited to the visible spectrum. In this paper, we focus on how to use the invisible spectra, most notably near-infrared (NIR) bands, to assist in visually enhancing old documents. Specifically, we demonstrate how to use the invisible bands to improve the visual quality of text-based documents corrupted with undesired artifacts such as ink-bleed, ink-corrosion, and foxing. For documents of line drawings that suffer from low contrast, we use details found in the invisible bands to enhance legibility. The key components of our framework involve detecting regions in the document that can be enhanced by the NIR spectra, compositing the enhanced gradient map using the NIR bands, and reconstructing the final image from the composited gradients. This work is part of a collaborative effort with the Nationaal Archief of the Netherlands (NAN) and Art Innovation, a manufacturer of hyperspectral imaging hardware designed specially for historical documents. Our approach is evaluated on historical documents from NAN that exhibit degradations common to documents found in most archives and libraries.

Introduction

Hyperspectral imaging (HSI) captures a densely sampled spectral response of a scene object over a broad spectrum including invisible spectra such as ultra-violet (UV) and near-infrared (NIR). Hyperspectral imaging has been employed in various scientific disciplines to provide valuable data for fields such as astronomy [1], [2], earth science and remote sensing [3], [4], and computer vision [5]. With the advances in technology and cost reductions, hyperspectral imaging of historical art works and documents is now accessible for use in national libraries and archives [6], [7].

One advantage of HSI in document imaging over the standard 3-channel imaging (i.e. RGB) is that HSI provides a detailed quantitative measurements of the document spectral response. Traditional RGB imaging, on the other hand, contains only a subset of the information available by combining response of all visible electro-magnetic (EM) radiation into three bands. This makes HSI more suitable for tasks that require accurate quantitative measurement such as conservation, detecting damage, and analysis of features in the document (e.g. ink and pigments) and changes over time due to aging or light exposure. In addition, hyperspectral imaging provides measurements in the invisible spectrums (NIR, UV) which further enrich the analysis and enhancement of the data. Measurements in the invisible spectral bands provide more information about the document being imaged by sometimes seeing more than the visible range and by sometimes seeing less. This is demonstrated by two examples in Fig. 1. For the first example, the NIR band at 900 nm (Fig. 1(b)) provides more salient gradient details than the document in the visible band at 500 nm (Fig. 1(a)). Conversely, for the second example, the NIR band at 800 nm (Fig. 1(d)) is better for guiding enhancement than the 450 nm visible band (Fig. 1(c)) since artifacts such as ink-bleed and ink-corrosion are less prevalent.

The goal of this paper is to take advantage of hyperspectral images of historical documents to visually enhance the document's content by exploiting additional information provided by the NIR bands. The visual enhancement in this paper is applied to the RGB image of the hyperspectral data as the RGB image is the most natural visualization of the data. In this work, we are interested in two tasks. For the text-based documents that are corrupted with artifacts such as ink-bleed, corrosion, and foxing, we use the invisible bands which capture much less artifacts than the visible bands to clean up the artifacts in the documents while preserving the look and the feel of the original document. For drawing-based documents that contain low contrast regions, we use NIR bands which capture more details than the visible bands to enhance the contrast in the documents. The data are enhanced in the gradient domain which has been shown to be effective for many computer vision tasks such as image editing [8], contrast adjustment [9], image stitching [10], and intrinsic image computation [11]. The key components of our algorithm include detecting regions that can be enhanced by the additional NIR spectral images, compositing the enhanced gradient map from NIR images, and reconstructing the final image from gradients using an optimization scheme.

This work is a part of ongoing collaborative effort with the Nationaal Archief of the Netherlands (NAN), one of Europe's leading research archives, and Art Innovation, a manufacturer of hyperspectral imaging hardware designed for historical documents. The documents processed in this paper, which are indicative to the type of artifacts common to historical documents, are imaged at the NAN using the SEPIA Quantitative Hyper-Spectral Imager (QHSI) device developed by Art Innovation [12]. The device performs hyperspectral imaging by capturing a very narrow spectral band of EM radiation one at a time by placing a bandpass filter in front of the light source to block out all but a selected band of the EM spectrum. A monochromatic camera is then used to capture the amount of light that is reflected by the document at that selected band. The filter is changed for each image, thus capturing different parts of EM spectrum to build up the HSI (Fig. 2).

The QSHI device captures images at different wavelength bands from 365 (UV) to 1100 nm (near-infrared (NIR)) with the step size of 10 nm in most cases except the bands in 300 and 1000 nm's. The images have the resolution of 4 mega pixels (2048×2048) for a physical surface area of 125 mm ×125 mm and are captured at 16 bit per pixel. Such high-resolution (approximately 256 pixels per mm²) provides a reliable spatial measurement suitable for even thin lines of handwriting and printed text.

The remainder of the paper is organized as follows: we begin by reviewing related work in Section 2. In Section 3, we introduce our algorithm for visually enhancing old documents using the hyperspectral data. We show experimental results in Section 4 and conclude with a discussion about our algorithm and future work.