How to Screen Capture Google Art Project Gigapixel Images Infinite Screen
J Imaging. 2021 Aug; 7(eight): 156.
Documenting Paintings with Gigapixel Photography
Pedro M. Cabezos-Bernal
1Departamento de Expresión Gráfica Arquitectónica, Universitat Politècnica de València, 46022 Valencia, Spain
Pablo Rodriguez-Navarro
2Centro de Investigación en Arquitectura, Patrimonio y Gestión para el Desarrollo Sostenible (PEGASO), Universitat Politècnica de València, 46022 Valencia, Spain; se.vpu@zeugirdor (P.R.-N.); se.vpu.historic period@ligt (T.One thousand.-P.)
Teresa Gil-Piqueras
twoCentro de Investigación en Arquitectura, Patrimonio y Gestión para el Desarrollo Sostenible (PEGASO), Universitat Politècnica de València, 46022 Valencia, Spain; se.vpu@zeugirdor (P.R.-Due north.); se.vpu.historic period@ligt (T.Grand.-P.)
Guillaume Caron, Academic Editor, Olga Regina Pereira Bellon, Academic Editor, and Ilan Shimshoni, Academic Editor
Received 2021 Jul 14; Accepted 2021 Aug 18.
Abstract
Digital photographic capture of pictorial artworks with gigapixel resolution (around 1000 megapixels or greater) is a novel technique that is beginning to be used by some of import international museums equally a means of documentation, assay, and broadcasting of their masterpieces. This line of inquiry is extremely interesting, not only for fine art curators and scholars but also for the general public. The results can be disseminated through online virtual museum displays, offering a detailed interactive visualization. These virtual visualizations allow the viewer to delve into the artwork in such a manner that it is possible to zoom in and detect those details, which would be negligible to the naked eye in a existent visit. Therefore, this kind of virtual visualization using gigapixel images has get an essential tool to enhance cultural heritage and to make it accessible to everyone. Since today'due south professional digital cameras provide images of around xl megapixels, obtaining gigapixel images requires some special capture and editing techniques. This commodity describes a series of photographic methodologies and equipment, adult past the squad of researchers, that have been put into exercise to achieve a very high level of detail and chromatic fidelity, in the documentation and dissemination of pictorial artworks. The result of this research work consisted in the gigapixel documentation of several masterpieces of the Museo de Bellas Artes of Valencia, one of the principal art galleries in Spain. The results will exist disseminated through the Internet, as volition exist shown with some examples.
Keywords: gigapixel photography, ultra-high resolution, fine art documentation, stitching, image registration, virtual musealization
1. Introduction
New techniques for the dissemination of cultural heritage through digital media is 1 of the lines of enquiry providing benefits to gild since the research results can exist available to the public by means online virtual museum displays. In fact, many important international museums [one], are using these technologies in collaboration with the multinational Google, which has developed its own loftier-resolution digital capture system for paintings. These works are exhibited on the Arts and Culture Project website [2], which contains many artworks that can be displayed with a loftier level of detail. They are digital reproductions with a gigapixel resolution, that is, a resolution greater than 1000 megapixels, which is l times greater than the epitome resolution provided by a conventional digital camera.
Gigapixel images allow documenting and analysing the paintings accurately, which is very useful for curators and art scholars. Furthermore, the virtual visualizations that tin exist generated from this type of epitome make the artwork accessible to anyone connected to the Internet. The viewers volition exist able to dive into the work, in such a way, that they would capeesh many details, which would exist negligible to the center in a real visit (Figure 1).
Hans Holbein the Younger, 1533, The Ambasssadors. Flick and detail obtained from Google Arts and Civilization [2].
Apart from Google, there are very few companies specialized in capturing gigapixel images of artworks due to the technical complexity and the specialized equipment. In that location are some examples, such as the French state arrangement Centre de Recherche et de Restauration des Musées de France CR2MF [three], the Italian company Haltadefinizione [4], or the Spanish Madpixel [5]. Some researchers have used gigapixel photography for documenting rupestrian paintings [6] and even combined with multispectral imaging techniques [seven]. Other research works have used gigapixel images for documenting large Baroque illusionistic paintings [8,9].
Digital photographic capture with gigapixel resolution is not an easy job and serious difficulties may arise due to physical issues such equally the diffraction of light, which represents a barrier that limits the sharpness that tin can be obtained with an optical device and a digital sensor. For this reason, the progression in the resolution of digital sensors has already reached the limit established by the diffraction of calorie-free and past the optical resolution provided past the lenses [10] that cannot match the resolution of the current top digital sensors. Going beyond this would not accept advantage of the constructive resolution of the sensor, unless the size of the optical-sensor assembly were increased, which is not practical for the futurity development of conventional cameras. In fact, at that place have been few attempts to develop prototype cameras providing gigapixel images on the fly. I of the first was the large format camera developed within the Gigapxl Project by Graham Flint in 2000 [11]. In this bulky photographic camera, the image was exposed on a 450 × 225 mm negative picture, which was later digitized to class a 4 gigapixel (Gp) epitome. Another more recent proposal is the Enlightened 2 gigapixel photographic camera, started by D. Brady and his team in 2012. This image included 98 micro-cameras with a combined resolution of ane Gp and it is still beingness developed and improved. The Aware x and forty models reach near 3 Gp. Nevertheless, such special prototypes are far from becoming an accessible pick due to their high complexity and cost.
A reasonable solution to overcome the trouble of diffraction and achieve gigapixel images using conventional cameras is multi-shot panoramic capture, which consists in obtaining a fix of photographs from the same point of view and with a sufficient overlap betwixt adjacent pictures and then that, by means of prototype stitching software, they tin can be joined to compose a college resolution paradigm [12].
In order to attain a perfect stitch between pictures and to avoid parallax errors, it is mandatory to use a panoramic head (Figure 2) to gear up the position of the optical eye or no-parallax point of the lens, while rotating the camera to obtain the unlike shots that will compose the final image. Moreover, a telephoto lens should be used then as to maximize the final resolution.
Manual and motorized panoramic heads.
The capture system developed by Google, called Art Camera [13], seem to exist based on this same principle, and consists of a photographic camera integrated in a panoramic head that progressively sweeps the painting from a fixed point. The partial images are afterwards processed by the multinational itself. This type of camera is not for sale and there are just a very limited number of units available exclusively to the company.
The capture systems used by other commercial companies such as Haltadefinizione, are not fully described, but some of them are based on using high-terminate digital reflex cameras and high-cost automatic panoramic heads by Clauss [fourteen]. Madpixel has his ain automatic panoramic head called MadpixelROB [15]. The aforementioned research works take also used the panoramic head methodology.
Using a panoramic head and a telephoto lens is a very effective method for documenting relatively small paintings with gigapixel resolution, but when it comes to capturing artworks of moderate size, in that location arise some drawbacks that limit image sharpness due to narrow depth of field provided by long focal length lenses. This trouble volition be discussed and fixed past post-obit the techniques that volition exist revealed below, since ane of the main aims of this commodity is to bear witness a new and very authentic gigapixel capture methodology that uses relatively affordable equipment. Moreover, the digital prototype processing to generate the gigapixel image and the dissemination of the results on the Internet volition be explained and carried out past means of opensource software.
ii. Materials and Methods
2.1. Capture Techniques
The photographic equipment that was used in this research work consisted of a 32.5 Mp digital camera Canon EOS 90D, equipped with a stock-still telephoto lens Canon EF 200 mm f2.8 L II USM, a Manfrotto tripod 28B and a Manfrotto panoramic head 303 SPH.
Long focal length lenses should be used to maximize resolution and the camera must exist quite shut to the artwork, and then that, in these circumstances, depth of field provided by the lens is very short. Furthermore, this is aggravated by the need to use an intermediate diaphragm aperture to avoid losing global sharpness by the event of calorie-free diffraction [xvi]. This problem causes a loss of sharpness in certain zones of the off-centred shots of the paintings, when using the panoramic head capture methodology. This is due to the athwart deviation between the camera sensor and the painting.
When the digital sensor remains parallel to the painting, all the points are perfectly focused, then the altitude between them and the sensor remain the same. Notwithstanding, as the camera is rotated towards the picture margins, the bending between the sensor and the painting increases dramatically (Figure three). This causes simply those points that are at the aforementioned altitude from the camera sensor equally the focused point to be perfectly sharp, while those remaining at different distances, will be gradually blurred due to narrow depth of field (Figure 4).
Obliquity between the shots and the canvas when using a panoramic head.
Loss of sharpness in an oblique shot due to narrow depth of field of long focal lenses.
To solve this problem, a new capture technique has been put into practice, which consists in taking the shots while moving the photographic camera parallel to the painting (Figure five). Doing so, the sharpness of the pictures will be always optimal and never limited past depth of field. However, while this method would solve the problem of sharpness, it also generates some difficulties that must be overcome. On the one hand, as the viewpoint would vary continuously, the lite reflected by the piece of work will change between the shots, causing slight differences in exposure and problems with specular reflections. Those problems tin can be solved past using a strategically placed controlled light source, which moves along with the camera.
Parallel camera translation to take all the pictures frontally to the canvass.
Another problem arises when it comes to joining the photo mosaic, obtained in that way, so most of the electric current software for stitching images would exist unable to bring together the mosaic when the viewpoint is not static. Fortunately, this trouble can be solved with the help of some stitching algorithms, initially developed by the High german professor Helmut Dersch [17], which were implemented in Hugin [18], an opensource stitching software with general public license that allows joining pictures taken from different viewpoints, as long equally they correspond a planar surface. Optionally, the commercial software PTGUI [nineteen] would besides do an excellent job when stitching these kinds of photomosaics.
Another way to construct the gigapixel prototype is by means SfM (structure from move) photogrammetry software, since the structure algorithm is conceived to generate a textured mesh from pictures taken from different viewpoints. The problem is that it would exist needed a greater number of shots since a minimum overlap of 50% between side by side pictures is advisable, while a 30% overlap would be fine when using stitching software. Yet, an advantage of using SfM photogrammetry software would be the 3D reconstruction of the painting and even the frame, which is not a plane surface, while stitching software would provide an accurate 2D rectified orthophoto of the canvas but not of the volumetric frame.
Taking into account the previous considerations, the following gigapixel capture techniques are proposed, which will be suitable for paintings or planar surfaces:
The single-viewpoint capture technique is a known and common methodology, which consist in using a panoramic caput to rotate the camera around the no-parallax point, which would be fixed and centred in front of the canvas, thus obtaining a set of overlapping pictures (Effigy 6). This technique requires limiting the obliquity of the shots in relation to the sheet in order to preserve the maximum image sharpness.
Single-viewpoint capture technique. The camera is rotated effectually its no-parallax point.
The parallel-multi-viewpoint capture technique is a new method, which consist in taking a mosaic of overlapped pictures every bit the camera is moved in parallel to the sail describing several rows or columns. The camera digital sensor must be parallel to the artwork, or, in other words, the lens optical axis should be orthogonal to the sail (Figure 7).
Parallel-multi-viewpoint capture technique. The camera moves parallel to the canvas.
The tilted-multi-viewpoint capture technique is a variation of the previous one, in which the camera can exist tilted if required. This option may seem awkward merely tin can be useful in the instance of capturing big paintings with a tripod that is not tall or short enough to permit the parallel move of the camera in front of the whole painting. In that case, the camera could be tilted when taking the upper or lower rows to cover the unabridged canvas. (Effigy 8).
Tilted-multi-viewpoint capture technique. The camera is moved mostly parallel to the canvas and tin can exist tilted if needed. Usually, only the upper or lower rows would be tilted.
The resolution of the final gigapixel image, achieved with those methods, will depend on several factors, such equally the camera sensor resolution, the lens focal length, and the distance between the canvass and the camera, as will be discussed later.
2.ii. Illumination Ready
When capturing paintings in that location are several approaches to illuminate the artwork properly. The simplest style is to use the museum's own illumination when the capture process is carried out in situ. Nevertheless, for a compatible and colour-authentic result information technology would exist appropriate to use defended and controlled light sources. In this research, there were used two Mettle 28 inch soft boxes lights, providing a colour temperature of 5500 Thousand and a CRI (Colour Rendering Index) greater than 90.
The soft boxes must be placed strategically to avoid specular reflections on the canvas and to guarantee lighting uniformity, so the lighting scheme proposed in Figure 9 is advisable. The lights must be placed outside the family of angles zone, equally otherwise specular reflections may occur.
Lighting scheme to illuminate the artwork uniformly. In order to avert specular reflections on the canvas, the lite sources must exist placed outside of the book defined by the family of angles.
When using the multi-viewpoint capture technique, it is mandatory to motility the lighting system along with the camera, and then a special mount was designed to attach the soft boxes to the tripod (Effigy 10). Additionally, a sliding system for the tripod's feet, which consisted in a two-wheeled aluminium bar, was also synthetic to facilitate the movement of the ready.
Lighting mountain to attach the lighting system to the tripod.
ii.iii. Camera Settings and Color Accuracy
Information technology is advisable to utilise an intermediate diaphragm discontinuity value to avoid the diffraction phenomenon while maintaining good depth of field. Setting the camera to f8 would be advisable as it is unremarkably the golden number for maximizing prototype sharpness. The photographic camera speed will depend on the lighting atmospheric condition. Tiresome speeds will not be a problem since a tripod is used.
The camera ISO value must be at the lower setting to avoid noisy pictures. An ISO 100 value is advisable. RAW Paradigm file format should exist used instead of JPG in other to maximize the dynamic range and to properly adjust the white balance and to apply an accurate colour profile during the digital developing process.
When using telephoto lenses, it is advisable to shoot the photographic camera remotely, even when a tripod is used. For this reason, it is recommended using a remote shooter or, even better, a mobile device or notepad with a compatible awarding for shooting the camera. In this inquiry, a notebook with the gratuitous software EOS Utility by Canon, was used to command the photographic camera via Wi-Fi.
In order to capture the colours of the artwork accurately, a Xrite ColorChecker chart was used to create a colour profile from a flick of the chart, which was illuminated by the scene lights (Figure 11). The colour profile was generated by the ColorChecker Camera Calibration software past Xrite and it can be used with RAW developers, such as the opensource RawTherapee [twenty], as well as with other commercial software, such as Adobe Camera Raw or Adobe Lightroom [21]. The picture of the chart can besides exist used as a reference to conform the proper white balance of all the shots at once, by using the middle grayness patch of the nautical chart to neutralize whatsoever colour predominance.
Reference flick with the 10-Rite ColorChecker chart that will help to fix the proper white balance and to create a specific colour contour for the lighting conditions.
ii.4. Generating the Gigapixel Epitome
In order to join the fix of pictures obtained with whatsoever of the aforementioned techniques, a stitching software such as Hugin or PTGUI can be used. As mentioned before, Hugin is a powerful opensource stitching software that can fifty-fifty summate the camera translation between shots, when the multi-viewpoint technique is used. The only drawback of Hugin is that is tedious when compared to the commercial culling PTGUI, which is incredibly fast.
The workflow with the stitching software is very unproblematic. Initially, the set up of pictures are analysed to automatically detect homologous points in the overlapping zones of the shots. So, the optimizer algorithm uses all these points to calculate the spatial position of every picture, which is divers by the pitch, yaw, and gyre angles. In addition to this, the camera translations, and the parameters to right the radial distortion, acquired past the lens, are also computed. The final stride allows rendering the set of pictures into a whole image at gigapixel resolution. The maximum final resolution will depend on the number of shots and their original resolution. That is estimated by the software so as to avoid incremental interpolations.
When using the multi-viewpoint technique, information technology is possible to assemble the gigapixel paradigm with an automated SfM photogrammetry software, such as Agisoft Metashape. Every bit mentioned before, using this kind of software would require a greater overlapping between adjacent shots and it is much more fourth dimension consuming. This option would exist interesting only when documenting volumetric artworks, such as altar pieces. The workflow for this kind of software begins with the decision of the camera positions from the analysis of the homologous points and the sparse point deject. Then, the dense cloud of the model tin be computed, and can be later triangulated to class a polygonal mesh. This mesh can be texturized past projecting the original pictures onto the mesh. Finally, an orthophoto of the 3D textured model can be generated at gigapixel resolution.
It should be mentioned that SfM photogrammetric techniques would not provide an admittedly accurate 3-dimensional restitution of those subtle surface details, merely since our chief objective is obtaining an orthophoto of the painting, it would provide first-class results. In social club to render fine surface properties of the painting, reflectance transformation imaging (RTI) would exist very useful, every bit well as other much more expensive 3D scanning techniques [22].
2.5. Canvas Measurement
Knowing the existent dimension of the paintings is important to provide an accurate scale of the gigapixel prototype. Usually the dimensions of the artwork are specified on the wall labels, but they are approximated. A Topcon Paradigm IS robotic total station was used for taking the measurement of the canvases without touching the artwork. This total station has a reflector-less measurement capability betwixt one.v and 250 m, providing a short-range precision of ±5 mm (MSE), and an angular precision of 0.3 mgon. The musical instrument was placed in front of the painting, and, with the aid of the telescopic sight, the corners of the canvas were identified. The coordinates of these points were obtained using TopSurv, a software that comes with the total station.
3. Results
In this section, some examples, which were captured using the described techniques, will be exposed. All the paintings vest to the Museo de Bellas Artes of Valencia (Spain).
3.ane. Single-Viewpoint Capture
The start case is focused on the artwork entitled La Santa Cena, painted by Juan de Juanes in 1534. This artwork measures 92.three cm tall × 85.viii cm wide. Due to its reduced size, it was shot using the Single-Viewpoint Technique. The camera was placed in a central position with respect to the sheet and at a altitude of two g. In this mode, the perimeter parts were not besides oblique to the camera sensor, thus preserving the image sharpness (Figure 12). All the zones had to be inside depth of field limits provided by the telephoto lens. The diaphragm was set to f8, the ISO value to 100, and the shutter speed was set up to 2 s in accordance with the lighting conditions.
Single-viewpoint capture technique. Viewpoint position in the capture of the Santa Cena by Juan de Juanes (1534). Museo de Bellas Artes de Valencia (Spain).
A full of 90 photographs were taken past rotating the camera around its eye of perspective, in steps of 2.five degrees (horizontal rotation), and iv degrees (vertical rotation). That resulted in a mosaic of 10 columns and 9 rows, with an overlapping between next pictures greater than 30% (Effigy 13a).
(a) Set of 90 pictures taken during the gigapixel capture. (b) Stitched gigapixel Paradigm.
A reference picture, with the X-Rite Color Checker Nautical chart, was taken to generate a specific colour profile for the lighting conditions of the scene, and to adjust the white balance in the RAW development process precisely. In this case, merely the lights of the museum were used as the lighting source.
The evolution process was carried out using the opensource software RAW Therapy. There were generated 90 files in TIF format with 32 $.25 per aqueduct, which were perfectly balanced with the colour profile created past the ColorChecker Photographic camera Calibration software, which is provided by the manufacturer of the colour chart.
After the raw development process, the mosaic was joined using Hugin, a GPL-licensed stitching software, which generated the last image (Figure 13b), with a resolution of 26,511 × 28,520 px, that is, 756 megapixels (0.76 gigapixels).
Information technology is interesting to express the resolution relative to a measurement unit, so this value would be independent of the artwork size. This parameter is known as pixel density and volition allow an objective comparison of the level of detail, acquired in each case. The pixel density, expressed in pixel per inch, was 787 ppi in this case.
Figure 14 shows a fragment of the resulting image in which the level of item can exist noticed. The pixel density is not huge considering of the long distance between the camera and the canvas. This distance was increased to prevent the loss of sharpness in the decentred shots due to the obliquity between the canvas and the camera sensor. Nevertheless, a greater resolution could take been achieved if the proposed parallel multi-viewpoint capture method had been used, so the camera would have been placed almost at the minimum focusing distance of the lens (1.v thousand instead of ii yard).
Fragment of the resulting gigapixel image.
3.2. Parallel Multi-Viewpoint Capture
The parallel multi-viewpoint capture method will produce better prototype quality than the previous one since the camera sensor is ever parallel to the canvas. Consequently, all the zones of the pictures would be perfectly focused. Withal, this arroyo is more complicated, so the camera must be moved along with the lights every shot, just it is worth it.
This technique was put into practice in the next case to capture the painting entitled Virgen de la Leche, painted by Bartolomé Bermejo around 1478. The canvas size is quite small, measuring 49.1 cm alpine × 34.5 cm wide.
In this case, the previously described lighting arrangement was used, which consisted of two soft boxed fastened to the tripod (Effigy 10). The lamps of the museum were turned-off and then equally not to mix different light sources.
The photographic set must exist stabilized after changing the camera position, and so the flexibility of the calorie-free stand up, which is fastened to the tripod, can atomic number 82 to slightly blurred shots due to small vibrations transmitted to the camera. This is controlled by monitoring the camera with the laptop. The live view prototype, which is received via Wi-Fi from the camera, is magnified 10× to detect any slight vibration and to focus the canvas very accurately. Once the image is completely steady and focused, the camera is remotely shot (Effigy 15).
Remote control of the camera with the laptop via Wi-Fi.
We took 20 shots to cover the unabridged canvas obtaining a mosaic of 5 columns and 4 rows with an overlapping greater than 30% (Figure 16a). The camera was placed at 1.5 thou from the canvas and moved horizontally to cover the upper row. And then, the camera was moved downwardly vertically to initiate the second row and and so on. A measuring tape was attached to the floor, parallel to the canvas, to serve every bit a reference for the translation movement. The diaphragm was gear up to f8, the ISO value to 100, and the shutter speed was set up to 1/20 of 2nd according to the lighting conditions.
(a) Set of twenty pictures taken during the gigapixel capture. (b) Stitched Gigapixel Image.
The raw developing process was carried out in the same way as the previous example. Nevertheless, the shots were stitched using PTGUI instead of Hugin as information technology is much faster. The resulting image (Figure 16b) has a final resolution of 14,183 × twenty,199 px, which provides a pixel density of 1044 ppi. This is much better than in the previous case, since the camera could be placed closer to the sail. As mentioned, in that location is no trouble with depth of field when using this method. Figure 17 shows a cropped fragment of the gigapixel image centred on the centre of the Virgin.
Fragment of the resulting gigapixel image.
three.iii. Tilted Multi-Viewpoint Capture
The last example shows the gigapixel capture of the artwork entitled Martirio de San Bartolomé, painted by Luca Giordano around 1650. The canvas size is 136 cm tall × 95 cm wide, which is a bit large to use the single-viewpoint method properly, so paradigm sharpness would be poor in some zones of the boundary shots. Moreover, the upper and lower borders of the painting exceeded the maximum and minimum height of the tripod, so the tilted multi-viewpoint capture method was chosen in this case.
Nosotros took 90 shots, forming a mosaic of 10 columns and 9 rows (Effigy 18a). Nearly of the pictures where parallel to the canvas. Only the shots respective to the upper and lower rows were slightly tilted vertically to cover the unabridged artwork, which is negligible for the image quality. The distance from the camera to the canvas was set up to 1.9 chiliad. The camera settings were: diaphragm f8, ISO 100, and photographic camera speed 1/5 of second, accordingly to the lighting atmospheric condition.
(a) Set of 90 pictures taken during the gigapixel capture. (b) Stitched gigapixel image.
Every bit in the previous cases, the RAW developing procedure was carried out with RAWTherapee to apply the proper white rest and the specific color profile to all the pictures at once. The stitching was carried out with PTGUI, which provided a gigapixel prototype (Figure eighteenb) with a total resolution of 30,884 × 44,228 px (1.36 gigapixels). In this instance, the pixel density was 826 ppi, something lower than in the previous case due to the larger distance between the camera and the canvas. Effigy xix shows a cropped fragment of the gigapixel image focused on the saint's mouth.
Fragment of the resulting gigapixel image.
iv. Discussion
The new proposed multi-viewpoint gigapixel capture techniques, compared to the conventional unmarried-viewpoint capture technique, improve the prototype quality of the resulting gigapixel image. The parallel multi-viewpoint gigapixel capture technique is, in full general, virtually recommended, so at that place is no loss of sharpness produced by narrow depth of field provided by telephoto lenses. The novel multi-viewpoint capture techniques imply using different shooting methods and moving the low-cal arrangement along with the photographic camera to avoid irresolute specular reflections during the capture process.
Nonetheless, the single-viewpoint capture technique can be also a proper method when the depth of field provides an acceptable sharpness in the whole motion-picture show. The acceptable sharpness would depend on the focal lens, the diaphragm aperture value, the focus distance, and the photographic camera sensor size. It can be calculated by using a complimentary DOF calculator such equally DOFMASTER [23].
From the experience acquired in this research, there are some practical considerations that tin can exist very useful for future researchers, which will be discussed here.
When documenting artworks with gigapixel resolution, the pixel density is an of import attribute to bear in mind when planning the photographic session. A pixel density range between 600 ppi and nearly 1000 ppi was established to guarantee an excellent level of detail of the paintings. The maximum reachable pixel density value is always imposed by the photographic equipment, so it depends on the lens focal length, the camera distance, and the camera sensor resolution and size.
In gild to maximize the pixel density, it would exist advisable to use long focal lenses and to place the camera as close to the painting as possible (the minimum focusing distance of the lens tin be the most limiting factor).
The pixel density of the final gigapixel epitome can be calculated hands by Equation (i), which tin be deduced geometrically:
where,
Pixel Density of the Image (ppc or ppi)
Sensor Width Resolution (px)
Lens Focal Length (mm)
Unit Conversion Factor [utilise 10 for obtaining the pixel density in pixels per centimetre (ppc), and 25.4 for pixels per inch (ppi)]
Camera Distance (mm)
Sensor Width (mm)
Obtaining a high pixel density is not necessarily a synonym of prototype quality, so a picture with a great pixel density can be totally blurred. For this reason, it is crucial to choose a lens providing excellent optical quality and to use information technology properly.
When using the proposed parallel multi-viewpoint technique, there is no problem with depth of field, so the camera sensor must remain parallel to the canvas always. The goal, in this instance, is focusing the camera on the canvass every bit accurately equally possible, maintaining the camera steady when shooting, and minimizing the loss of sharpness caused by the lens diffraction.
In order to do so, information technology is necessary to employ a tripod to maintain the camera totally stabilized. A measuring tape tin be placed on the floor, parallel to the canvass, to piece of work every bit a guide for the tripod legs so equally to maintain the same distance from the photographic camera to the sail.
Additionally, it is advisable to focus and shoot the photographic camera remotely to avoid small movements that would produce slightly blurred images. This tin be done by using a computer or a mobile device with the software provided by the camera. The previous aspects are critical, especially when using long focal lenses in which any small movement would be extremely amplified on the camera sensor.
Moreover, setting the ISO setting to its minimum is mandatory to better the paradigm quality, too as setting the proper exposure values to capture the unabridged dynamic range of the scene. In this sense, it is appropriate to gear up the aperture to medium values, such as f8. Intermediate apertures would maximize the epitome sharpness, while fugitive diffraction problems. Once the aperture is ready, the shutter speed can exist determined appropriately to the diaphragm aperture to obtain the proper exposure. Visualizing the alive histogram at this point tin be very helpful to avoid clipping areas.
The image mosaic can be planned before starting the capture to know both the horizontal and the vertical camera displacements, likewise equally the full corporeality of shots that will be necessary to cover the entire painting. Equally mentioned before, a minimum overlap of about 30% betwixt side by side shots is advisable for a successful stitching. It is also recommended to shoot the photographic camera in portrait mode to reduce the vertical photographic camera movements, which are less convenient than the horizontal ones.
The camera vertical displacement can be determined by Equation (2):
(2)
where,
Photographic camera Vertical Displacement (mm)
Camera Distance (mm)
Sensor Width (mm)
Image Overlap Percentage (%) (a minimum of thirty% is advisable)
Lens Focal Length (mm)
The camera horizontal displacement can exist hands calculated as a fraction of the vertical deportation, so the sensor aspect ratio is known:
where,
Photographic camera Horizontal Displacement (mm)
Camera Vertical Deportation (mm)
Sensor Aspect Ratio (ordinarily 3:ii for professional cameras)
The total amount of shots composing the Photographic Mosaic (Rows and Columns) can be predicted as follows:
where,
Number of Rows of the Photographic Mosaic
Number of Columns of the Photographic Mosaic
Painting Height (mm)
Painting Width (mm)
Photographic camera Horizontal Displacement (mm)
Camera Vertical Displacement (mm)
A prediction of the resolution of the final gigapixel image in Gigapixels can be obtained from the side by side equation:
where,
Total Resolution of the Gigapixel Image (Gp)
Painting Height (cm)
Painting Width (cm)
Pixel Density of the Image (ppc)
As explained before, the resulting mosaic could exist assembled with free stitching software, such as Hugin or with commercial ane, such as PTGUI, which is very straightforward and fast. The resulting gigapixel epitome tin can be very heavy and difficult to handle unless a powerful computer is used. Fortunately, the dissemination of such heavy gigapixel images through the Net tin can be carried out by decomposing the image in a multiresolution mosaic, which is besides chosen pyramidal image. The process consists in applying an algorithm that generates unlike tiles from the gigapixel image, with different sizes and levels of resolution. And so, these image tiles can exist loaded progressively in real fourth dimension by using a specific html5 viewer. In this way, when the user demands more definition by zooming up, the viewer loads only the specific tiles for the visualization area.
When visualizing the resulting multiresolution mosaic through the Internet, there is no need to use powerful equipment, since even a conventional smartphone tin manage this kind of pyramidal image. This technique is used in very well-known applications such as Google Maps or Google Earth.
It is important to mention that, due to the different kinds of display that the spectators can utilise for the visualization of the images online, information technology is advisable to generate the multiresolution mosaic using the standard colour profile sRGB, which is suitable for most of the devices. Notwithstanding, the accuracy of the colour reproduction will depend on the gamut of the display and its proper calibration.
Zoomify [23] is ane of the software packages that tin provide multiresolution mosaics and has its own viewers, including a free version. At that place are another powerful opensource viewers, such every bit OpenSeadragon [24], which is the one used for this project.
Equally a consequence, the gigapixel images that have been shown in this commodity can be visualized online by using the QR codes on Effigy 20 or past following the links at the caption.
The rest of the museum imaging procedure tin be solved using a proper web page pattern and this may depend on the needs of the researchers. In this case, Elementor [25], a uncomplicated and free web blueprint plugin based on WordPress [26], was used to develop the entire webpage that permit the results to exist disseminated: www.gpix.upv.es (accessed on 19 August 2021).
Acknowledgments
Nosotros warmly appreciate the collaboration of the Museo de Bellas Artes de Valencia (Kingdom of spain) for their back up and access to the artworks. We want to specially thank its current director, Pablo González, as well every bit his predecessors, Carlos Reyero and José Ignacio Casar. We wish too to recognize and thank Pilar Gramage, Ramón Martínez and Juan Toledo for their valuable assistance.
Author Contributions
Photographic capture and Paradigm Editing, P.K.C.-B., P.R.-N. and T.G.-P.; Topographic measurements and SfM restitutions P.R.-North. and T.M.-P.; Visualization techniques and dissemination, P.M.C.-B. All authors have read and agreed to the published version of the manuscript.
Funding
This enquiry was carried out within the Inquiry Project entitled Captura fotográfica de resolución gigapíxel para la documentación y divulgación del patrimonio pictórico (01/01/19–01/01/21), reference SP20180066. Project funded with the help of Primeros Proyectos de Investigación (PAID-06-18), Vicerrectorado de Investigación, Innovación y Transferencia de la Universitat Politècnica de València (UPV), València, Spain.
Conflicts of Interest
The authors declare no conflict of interest.
Footnotes
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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8404936/
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