Colorimetric and spectral analysis of rock art by means of the characterization of digital sensors

Tesis por compendio[ES] Las labores de documentación de arte rupestre son arduas y delicadas, donde el color desempeña un papel fundamental, proporcionando información vital a nivel descriptivo, técnico y cuantitativo . Tradicionalmente los métodos de documentación en arqueología quedaban restringidos a procedimientos estrictamente subjetivos. Sin embargo, esta metodología conlleva limitaciones prácticas y técnicas, afectando a los resultados obtenidos en la determinación del color. El empleo combinado de técnicas geomáticas, como la fotogrametría o el láser escáner, junto con técnicas de procesamiento de imágenes digitales, ha supuesto un notable avance. El problema es que, aunque las imágenes digitales permiten capturar el color de forma rápida, sencilla, y no invasiva, los datos RGB registrados por la cámara no tienen un sentido colorimétrico riguroso. Se requiere la aplicación de un proceso riguroso de tranformación que permita obtener datos fidedignos del color a través de imágenes digitales. En esta tesis se propone una solución científica novedosa y de vanguardia, en la que se persigue integrar el análisis espectrofotométrico y colorimétrico como complemento a técnicas fotogramétricas que permitan una mejora en la identificación del color y representación de pigmentos con máxima fiabilidad en levantamientos, modelos y reconstrucciones tridimensionales (3D). La metodología propuesta se basa en la caracterización colorimétrica de sensores digitales, que es de novel aplicación en pinturas rupestres. La caracterización pretende obtener las ecuaciones de transformación entre los datos de color registrados por la cámara, dependientes del dispositivo, y espacios de color independientes, de base física, como los establecidos por la Commission Internationale de l'Éclairage (CIE). Para el tratamiento de datos colorimétricos y espectrales se requiere disponer de un software de características técnicas muy específicas. Aunque existe software comercial, lo cierto es que realizan por separado el tratamiento digital de imágenes y las operaciones colorimétricas. No existe software que integre ambas, ni que además permita llevar a cabo la caracterización. Como aspecto fundamental, presentamos en esta tesis el software propio desarrollado, denominado pyColourimetry, siguiendo las recomendaciones publicadas por la CIE, de código abierto, y adaptado al flujo metodológico propuesto, de modo que facilite la independencia y el progreso científico sin ataduras comerciales, permitiendo el tratamiento de datos colorimétricos y espectrales, y confiriendo al usuario pleno control del proceso y la gestión de los datos obtenidos. Adicinalmente, en este estudio se expone el análisis de los principales factores que afectan a la caracterización tales como el sensor empleado, los parámetros de la cámara durante la toma, la iluminación, el modelo de regresión, y el conjunto de datos empleados como entrenamiento del modelo. Se ha aplicado un modelo de regresión basado en procesos Gaussianos, y se ha comparado con los resultados obtenidos mediante polinomios. También presentamos un nuevo esquema de trabajo que permite la selección automática de muestras de color, adaptado al rango cromático de la escena, que se ha denominado P-ASK, basado en el algoritmo de clasificación K-means. Los resultados obtenidos en esta tesis demuestran que el proceso metodológico de caracterización propuesto es altamente aplicable en tareas de documentación y preservación del patrimonio cultural en general, y en arte rupestre en particular. Se trata de una metodología de bajo coste, no invasiva, que permite obtener el registro colorimétrico de escenas completas. Una vez caracterizada, una cámara digital convencional puede emplearse para la determinación del color de forma rigurosa, simulando un colorímetro, lo que permitirá trabajar en un espacio de color de base física, independiente del dispositivo y comparable con[CA] Les tasques de documentació gràfica d'art rupestre són àrdues i delicades, on el color compleix un paper fonamental, proporcionant informació vital a nivell descriptiu, t\`ecnic i quantitatiu.Tradicionalment els mètodes de documentació en arqueologia quedaven restringits a procediments estrictament subjectius, comportant limitacions pràctiques i tècniques, afectant els resultats obtinguts en la determinació de la color. L'ús combinat de tècniques geomàtiques, com la fotogrametria o el làser escàner, juntament amb tècniques de processament i realç d'imatges digitals, ha suposat un notable avanç. Tot i que les imatges digitals permeten capturar el color de forma ràpida, senzilla, i no invasiva, les dades RGB proporcionades per la càmera no tenen un sentit colorimètric rigorós. Es requereix l'aplicació d'un procés rigorós de transformació que permeti obtenir dades fidedignes de la color a través d'imatges digitals. En aquesta tesi es proposa una solució científica innovadora i d'avantguarda, en la qual es persegueix integrar l'anàlisi espectrofotomètric i colorimètric com a complement a tècniques fotogramètriques que permetin una millora en la identificació de la color i representació de pigments amb màxima fiabilitat en aixecaments, models i reconstruccions tridimensionals 3D. La metodologia proposada es basa en la caracterització colorimètrica de sensors digitals, que és de novell aplicació en pintures rupestres. La caracterització pretén obtenir les equacions de transformació entre les dades de color registrats per la càmera, dependents d'el dispositiu, i espais de color independents, de base física, com els establerts per la Commission Internationale de l'Éclairage (CIE). Per al tractament de dades colorimètriques i espectrals de forma rigorosa es requereix disposar d'un programari de característiques tècniques molt específiques. Encara que hi ha programari comercial, fan per separat el tractament digital d'imatges i les operacions colorimètriques. No hi ha programari que integri totes dues, ni que permeti dur a terme la caracterització. Com a aspecte addicional i fonamental, vam presentar el programari propi que s'ha desenvolupat, denominat pyColourimetry, segons les recomanacions publicades per la CIE, de codi obert, i adaptat al flux metodológic proposat, de manera que faciliti la independència i el progrés científic sense lligams comercials, permetent el tractament de dades colorimètriques i espectrals, i conferint a l'usuari ple control del procés i la gestió de les dades obtingudes. A més, s'exposa l'anàlisi dels principals factors que afecten la caracterització tals com el sensor emprat, els paràmetres de la càmera durant la presa, il¿luminació, el model de regressió, i el conjunt de dades emprades com a entrenament d'el model. S'ha aplicat un model de regressió basat en processos Gaussians, i s'han comparat els resultats obtinguts mitjançant polinomis. També vam presentar un nou esquema de treball que permet la selecció automàtica de mostres de color, adaptat a la franja cromàtica de l'escena, que s'ha anomenat P-ASK, basat en l'algoritme de classificació K-means. Els resultats obtinguts en aquesta tesi demostren que el procés metodològic de caracterització proposat és altament aplicable en tasques de documentació i preservació de el patrimoni cultural en general, i en art rupestre en particular. Es tracta d'una metodologia de baix cost, no invasiva, que permet obtenir el registre colorimètric d'escenes completes. Un cop caracteritzada, una càmera digital convencional pot emprar-se per a la determinació de la color de forma rigorosa, simulant un colorímetre, el que permetrà treballar en un espai de color de base física, independent d'el dispositiu i comparable amb dades obtingudes mitjançant altres càmeres que tambè estiguin caracteritzades.[EN] Cultural heritage documentation and preservation is an arduous and delicate task in which color plays a fundamental role. The correct determination of color provides vital information on a descriptive, technical and quantitative level. Classical color documentation methods in archaeology were usually restricted to strictly subjective procedures. However, this methodology has practical and technical limitations, affecting the results obtained in the determination of color. Nowadays, it is frequent to support classical methods with geomatics techniques, such as photogrammetry or laser scanning, together with digital image processing. Although digital images allow color to be captured quickly, easily, and in a non-invasive way, the RGB data provided by the camera does not itself have a rigorous colorimetric sense. Therefore, a rigorous transformation process to obtain reliable color data from digital images is required. This thesis proposes a novel technical solution, in which the integration of spectrophotometric and colorimetric analysis is intended as a complement to photogrammetric techniques that allow an improvement in color identification and representation of pigments with maximum reliability in 3D surveys, models and reconstructions. The proposed methodology is based on the colorimetric characterization of digital sensors, which is of novel application in cave paintings. The characterization aims to obtain the transformation equations between the device-dependent color data recorded by the camera and the independent, physically-based color spaces, such as those established by the Commission Internationale de l'Éclairage (CIE). The rigorous processing of color and spectral data requires software packages with specific colorimetric functionalities. Although there are different commercial software options, they do not integrate the digital image processing and colorimetric computations together. And more importantly, they do not allow the camera characterization to be carried out. Therefore, as a key aspect in this thesis is our in-house pyColourimetry software that was developed and tested taking into account the recommendations published by the CIE. pyColourimetry is an open-source code, independent without commercial ties; it allows the treatment of colorimetric and spectral data and the digital image processing, and gives full control of the characterization process and the management of the obtained data to the user. On the other hand, this study presents a further analysis of the main factors affecting the characterization, such as the camera built-in sensor, the camera parameters, the illuminant, the regression model, and the data set used for model training. For computing the transformation equations, the literature recommends the use of polynomial equations as a regression model. Thus, polynomial models are considered as a starting point in this thesis. Additionally, a regression model based on Gaussian processes has been applied, and the results obtained by means of polynomials have been compared. Also, a new working scheme was reported which allows the automatic selection of color samples, adapted to the chromatic range of the scene. This scheme is called P-ASK, based on the K-means classification algorithm. The results achieved in this thesis show that the proposed framework for camera characterization is highly applicable in documentation and conservation tasks in general cultural heritage applications, and particularly in rock art painting. It is a low-cost and non-invasive methodology that allows for the colorimetric recording from complete image scenes. Once characterized, a conventional digital camera can be used for rigorous color determination, simulating a colorimeter. Thus, it is possible to work in a physical color space, independent of the device used, and comparable with data obtained from other cameras that are also characterized.Thanks to the Universitat Politècnica de València for the FPI scholarshipMolada Tebar, A. (2020). Colorimetric and spectral analysis of rock art by means of the characterization of digital sensors [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/160386TESISCompendi

Evaluation and optimal design of spectral sensitivities for digital color imaging

The quality of an image captured by color imaging system primarily depends on three factors: sensor spectral sensitivity, illumination and scene. While illumination is very important to be known, the sensitivity characteristics is critical to the success of imaging applications, and is necessary to be optimally designed under practical constraints. The ultimate image quality is judged subjectively by human visual system. This dissertation addresses the evaluation and optimal design of spectral sensitivity functions for digital color imaging devices. Color imaging fundamentals and device characterization are discussed in the first place. For the evaluation of spectral sensitivity functions, this dissertation concentrates on the consideration of imaging noise characteristics. Both signal-independent and signal-dependent noises form an imaging noise model and noises will be propagated while signal is processed. A new colorimetric quality metric, unified measure of goodness (UMG), which addresses color accuracy and noise performance simultaneously, is introduced and compared with other available quality metrics. Through comparison, UMG is designated as a primary evaluation metric. On the optimal design of spectral sensitivity functions, three generic approaches, optimization through enumeration evaluation, optimization of parameterized functions, and optimization of additional channel, are analyzed in the case of the filter fabrication process is unknown. Otherwise a hierarchical design approach is introduced, which emphasizes the use of the primary metric but the initial optimization results are refined through the application of multiple secondary metrics. Finally the validity of UMG as a primary metric and the hierarchical approach are experimentally tested and verified

Color Managing for Papers Containing Optical Brightening Agents

The role of a color-managed inkjet proof is to predict and simulate the visual appearance of printed color. The proof-to-print visual match works well under different viewing conditions when the input ICC profile and the output ICC profile, built from characterization datasets, do not contain optical brightening agents (OBA). OBAs influence printed color when measured for characterization and viewed. These brightening agents absorb UV wavelengths in the illuminant and fluoresce in the blue wavelengths. As more and more OBAs are used in printing paper production, the role of color proofing becomes more difficult. The difference in the amount of the UV component of the measuring and viewing light sources cause a problem where the OBA effect, as measured, may not be the same amount of OBA effect that should be proofed under the viewing illuminant. There are two objectives in this research project. The first objective is to show how printed colors, under identical printing conditions on OBA and non-OBA substrates, look different than when they are proofed using current characterization for proofing practices. Both M0 (UV-included) and M2 (UV-cut) measurement data are collected from color patches with selected tonal values and input ICC profiles created from this data are used to proof the brightened reference print. The results show that the UV-cut characterization treatment produces a very poor proof to the reference, while the UV-included proof was ranked as a fairly high match. A third commercially available software designed to improve upon the UV-included treatment, the X-Rite Optical Brightened Compensation module, was also tested and found to be a good match to the reference as well. The second objective is to propose different ways the characterization data can be adjusted for the OBAs in a reference print on brightened paper, by accounting for the influence of UV in the measurement illuminant, and the influence of UV in the viewing illuminant. By means of psychometric analyses, the results show that (1) the proof-to- print match is the worst when OBA in print and UV in the measurement illuminant are not addressed (UV-cut characterization data from M2); (2) although not conclusive, the proof-to-print match improves when OBA in print, UV in the measurement illuminant (characterization data from M0), and UV in the viewing illuminant are addressed

Method for hue plane preserving color correction

Hue plane preserving color correction (HPPCC), introduced by Andersen and Hardeberg [Proceedings of the 13th Color and Imaging Conference (CIC) (2005), pp. 141–146], maps device-dependent color values (RGB) to colorimetric color values (XYZ) using a set of linear transforms, realized by white point preserving 3×33×3 matrices, where each transform is learned and applied in a subregion of color space, defined by two adjacent hue planes. The hue plane delimited subregions of camera RGB values are mapped to corresponding hue plane delimited subregions of estimated colorimetric XYZ values. Hue planes are geometrical half-planes, where each is defined by the neutral axis and a chromatic color in a linear color space. The key advantage of the HPPCC method is that, while offering an estimation accuracy of higher order methods, it maintains the linear colorimetric relations of colors in hue planes. As a significant result, it therefore also renders the colorimetric estimates invariant to exposure and shading of object reflection. In this paper, we present a new flexible and robust version of HPPCC using constrained least squares in the optimization, where the subregions can be chosen freely in number and position in order to optimize the results while constraining transform continuity at the subregion boundaries. The method is compared to a selection of other state-of-the-art characterization methods, and the results show that it outperforms the original HPPCC method

Print-to-Proof Visual Match Using Papers with Optical Brightening Agents

Optical Brightening Agents (OBAs) are chemicals added to paper pulp whose purpose is to brighten the white point of the paper. Adding OBAs results in a brighter white, increased tonal range, and more chromatic colors. However, adding OBAs can also create problems in visual print-to-proof match where proofing substrates do not contain OBAs. Visual print-to-proof match is the final judge of conformance in a print business. When printing and proofing in conformance to standards and specifications on non-OBA papers, there is visual match between the print and the proof. Printing on OBA loaded papers causes two main problems: (1) difficulty in achieving conformance to printing standards and (2) visual print-to-proof mismatch. To solve the above problems, this research begins by adopting the new M1 measurement condition and the revised ISO 3664:2009 viewing conditions. It then assumes that the print on OBA loaded paper is the anchor and the proof must be color managed to match the print using these new measurement and viewing conditions. In order to test the proposed solution, the researcher prepared a series of prints and proofs that (1) reproduced the proof-to-print match traditionally achieved on non-OBA loaded printing papers (the anchor pair), (2) reproduced the proof-to-print mismatch on OBA loaded printing papers (the problem pair), ix and (3) tested the color managed approach to solving the problem described above (the solution pair). Finally, these pairs were evaluated by a panel of observers in a paired comparison experiment under the revised ISO 3664:2009 viewing conditions. The results of the paired comparison experiment first demonstrated that the researcher could reproduced both a proof-to-print match on non-OBA loaded papers and a proof-to-print mismatch on OBA loaded papers. In addition, the solution pair was demonstrated to be preferred to all other pairs at the .05 level of significance. Finally CIELAB plots of the problem pair and the solution pair under M1 conditions supported the results of the pair comparison experiment. Under M1 conditions the proof-to-print mismatch (difference in CIELAB values) for the problem pair was shown to be approximately twice as large as the proof-to-print mismatch for the solution pair. Based on the results of this research, the proposed solution was shown to be a promising approach for solving the industry wide problem of print-to-proof mismatch when printers print on OBA loaded papers

FROM DOCUMENTATION IMAGES TO RESTAURATION SUPPORT TOOLS: A PATHFOLLOWING THE NEPTUNE FOUNTAIN IN BOLOGNA DESIGN PROCESS

The sixteenth-century Fountain of Neptune is one of Bologna's most renowned landmarks. During the recent restoration activities of the monumental sculpture group, consisting in precious marbles and highly refined bronzes with water jets, a photographic campaign has been carried out exclusively for documentation purposes of the current state of preservation of the complex. Nevertheless, the highquality imagery was used for a different use, namely to create a 3D digital model accurate in shape and color by means of automated photogrammetric techniques and a robust customized pipeline. This 3D model was used as basic tool to support many and different activities of the restoration site. The paper describes the 3D model construction technique used and the most important applications in which it was used as support tool for restoration: (i) reliable documentation of the actual state; (ii) surface cleaning analysis; (iii) new water system and jets; (iv) new lighting design simulation; (v) support for preliminary analysis and projectual studies related to hardly accessible areas; (vi) structural analysis; (vii) base for filling gaps or missing elements through 3D printing; (viii) high-quality visualization and rendering and (ix) support for data modelling and semantic-based diagrams

PHOTOGRAMMETRY DRIVEN TOOLS TO SUPPORT THE RESTORATION OF OPEN-AIR BRONZE SURFACES OF SCULPTURES: AN INTEGRATED SOLUTION STARTING FROM THE EXPERIENCE OF THE NEPTUNE FOUNTAIN IN BOLOGNA

Checking the irreversible process of clean-up is a delicate task that requires a work of synthesis between theoretical knowledge and practical experience, to define an effective operating protocol on a limited patch area to be extended later to the entire artefact's surface. In this paper, we present a new, quick, semi-automated 3D photogrammetry-based solution to support restorers in the open-air bronze artwork cleaning from corrosion and weathering decay. The solution allows the conservators to assess in real time and with a high level of fidelity in colour and shape, the 'surfaces' to be cleaned before, during and after the clear-out treatment. The solution besides allows an effective and valuable support tool for restorers to identify the original layer of the bronze surface, developed and validated during the ongoing restoration of the Neptune Fountain in Bologna

Individual Colorimetric Observers for Personalized Color Imaging

Colors are typically described by three values such as RGB, XYZ, and HSV. This is rooted to the fact that humans possess three types of photoreceptors under photopic conditions, and human color vision can be characterized by a set of three color matching functions (CMFs). CMFs integrate spectra to produce three colorimetric values that are related to visual responses. In reality, large variations in CMFs exist among color-normal populations. Thus, a pair of two spectrally different stimuli might be a match for one person but a mismatch for another person, also known as observer metamerism. Observer metamerism is a serious issue in color-critical applications such as soft proofing in graphic arts and color grading in digital cinema, where colors are compared on different displays. Due to observer metamerism, calibrated displays might not appear correctly, and one person might disagree with color adjustments made by another person. The recent advent of wide color gamut display technologies (e.g., LEDs, OLEDs, lasers, and Quantum Dots) has made observer metamerism even more serious due to their spectrally narrow primaries. The variations among normal color vision and observer metamerism have been overlooked for many years. The current typical color imaging workflow uses a single standard observer assuming all the color-normal people possess the same CMFs. This dissertation provides a possible solution for observer metamerism in color-critical applications by personalized color imaging introducing individual colorimetric observers. In this dissertation, at first, color matching data were collected to derive and validate CMFs for individual colorimetric observers. The data from 151 color-normal observers were obtained at four different locations. Second, two types of individual colorimetric observer functions were derived and validated. One is an individual colorimetric observer model, an extension of the CIE 2006 physiological observer incorporating eight physiological parameters to model individuals in addition to age and field size inputs. The other is a set of categorical observer functions providing a more convenient approach towards the personalized color imaging. Third, two workflows were proposed to characterize human color vision: one using a nomaloscope and the other using proposed spectral pseudoisochromatic images. Finally, the personalized color imaging was evaluated in a color image matching study on an LCD monitor and a laser projector and in a perceived color difference study on a SHARP Quattron display. The personalized color imaging was implemented using a newly introduced ICC profile, iccMAX