Jouni Hiltunen

Unsupervised filtering of color spectra

We describe a class of unsupervised systems that extract features from databases of reflectance spectra that sample color space in a way that reflects the properties of human color perception. The systems find the internal weight coefficients by optimizing an energy function. We describe several energy functions based on second- and fourth-order statistical moments of the computed output values. We also investigate the effects of imposing boundary conditions on the filter coefficients and the performance of the resulting systems for the databases with the reflectance spectra. The experiments show that the weight matrix for one of the systems is very similar to the eigenvector system, whereas the second type of system tries to rotate the eigenvector system in such a way that the resulting filters partition the spectrum into different bands. We also show how the system can be forced to use weight vectors with positive coefficients. Systems consisting of positive weight vectors are then approximated with Gaussian quadrature methods. In the experimental part of the paper we investigate the properties of three databases consisting of reflectance spectra. We compare the statistical structure of the different databases and investigate how these systems can be used to explore the structure of the space of reflectance spectra.

Extending Diabetic Retinopathy Imaging from Color to Spectra

In this study, spectral images of 66 human retinas were collected. These spectral images were measured in vivo from 54 voluntary diabetic patients and 12 control subjects using a modified ophthalmic fundus camera system. This system incorporates the optics of a standard fundus microscope, 30 narrow bandpass interference filters ranging from 400 to 700 nanometers at 10 nm intervals, a steady-state broadband lightsource and a monochrome digital charge-coupled device camera. The introduced spectral fundus image database will be expanded in the future with professional annotations and will be made public.

Thermal and hyperspectral imaging for Norway spruce (Picea abies) seeds screening

Hyperspectral and thermal lifetime imaging were used to assess spruce seed quality.Viable, empty and infested seeds were resolved with high accuracy with both methods.400-1000nm data was not as informative as 1000-2500nm and thermal decay data.Classification of 93% accuracy was obtained using three wavelengths in SWIR range.The results suggest that high-throughput spruce seed quality testing is possible. The quality of seeds used in agriculture and forestry is tightly linked to the plant productivity. Thus, the development of high-throughput nondestructive methods to classify the seeds is of prime interest. Visible and near infrared (VNIR, 400-1000nm range) and short-wave infrared (SWIR, 1000-2500nm range) hyperspectral imaging techniques were compared to an infrared lifetime imaging technique to evaluate Norway spruce (Picea abies (L.) Karst.) seed quality. Hyperspectral image and thermal data from 1606 seeds were used to identify viable seeds, empty seeds and seeds infested by Megastigmus sp. larvae. The spectra of seeds obtained from hyperspectral imaging, especially in SWIR range and the thermal signal decay of seeds following an exposure to a short light pulse were characteristic of the seed status. Classification of the seeds to three classes was performed with a Support Vector Machine (nu-SVM) and sparse logistic regression based feature selection. Leave-One-Out classification resulted to 99% accuracy using either thermal or spectral measurements compared to radiography classification. In spectral imaging case, all important features were located in the SWIR range. Furthermore, the classification results showed that accurate (93.8%) seed sorting can be achieved with a simpler method based on information from only three hyperspectral bands at 1310nm, 1710nm and 1985nm locations, suggesting a possibility to build an inexpensive screening device. The results indicate that combined classification methods with hyperspectral imaging technique and infrared lifetime imaging technique constitute practically high performance fast and non-destructive techniques for high-throughput seed screening.

Color and Image Characterization of a Three CCD Seven Band Spectral Camera

In this study spectral and spatial characterization of a seven channel FluxData 1665 MS7 three-CCD spectral video camera was performed in terms of the sensor spectral sensitivity, linearity, spatial uniformity, noise and spatial alignment. The results indicate small deviation from ideal linear sensor response. Also, a small spatial non-uniformity and systematic shift exists between the channel images. However, images were observed to have high quality in term of noise. Spectral characterization showed that the sensor has good response in the 380-910 nm region with only some sensitivity limitations in the 715-740 nm range. We also evaluated the spectral reflectance estimation in 400-700 nm range using empirical regression methods and the Digital ColorChecker SG and ColorChecker charts. These experiments resulted in average ΔE00 color accuracy of 1.6 – 2.4 units, depending on the illuminant and estimation method.

Accuracy in Colour Reproduction: Using a ColorChecker Chart to Assess the Usefulness and Comparability of Data Acquired with Two Hyper-Spectral Systems

Hyper-spectral imaging has been applied as an in situ technique for the study and accurate digital documentation of coloured artworks. Providing spectral and colorimetric characterisation across the entire surface of an object, it can be used to identify the coloured materials, measure colour changes, and document it with high fidelity. However, depending on the system used, data accuracy and reliability may vary. In this work, developed within the Round Robin Test being carried out by COSCH Working Group 1, an X-Rite® ColorChecker Classic chart was analysed with two push-broom hyper-spectral systems developed by different groups (IFAC-CNR and IP-UEF), in the 400-1000 nm range, and the data obtained were compared. This comparison allowed to assess the accuracy of colour reproduction processes performed by the two systems. The results obtained are satisfactory in terms of spectral and colorimetric accuracy for some colours, but show differences at both ends of the visible range.

Accurate spectral color measurements

Surface color measurement is of importance in a very wide range of industrial applications including paint, paper, printing, photography, textiles, plastics and so on. For a demanding color measurements spectral approach is often needed. One can measure a color spectrum with a spectrophotometer using calibrated standard samples as a reference. Because it is impossible to define absolute color values of a sample, we always work with approximations. The human eye can perceive color difference as small as 0.5 CIELAB units and thus distinguish millions of colors. This 0.5 unit difference should be a goal for the precise color measurements. This limit is not a problem if we only want to measure the color difference of two samples, but if we want to know in a same time exact color coordinate values accuracy problems arise. The values of two instruments can be astonishingly different. The accuracy of the instrument used in color measurement may depend on various errors such as photometric non-linearity, wavelength error, integrating sphere dark level error, integrating sphere error in both specular included and specular excluded modes. Thus the correction formulas should be used to get more accurate results. Another question is how many channels i.e. wavelengths we are using to measure a spectrum. It is obvious that the sampling interval should be short to get more precise results. Furthermore, the result we get is always compromise of measuring time, conditions and cost. Sometimes we have to use portable syste or the shape and the size of samples makes it impossible to use sensitive equipment. In this study a small set of calibrated color tiles measured with the Perkin Elmer Lamda 18 and the Minolta CM-2002 spectrophotometers are compared. In the paper we explain the typical error sources of spectral color measurements, and show which are the accuracy demands a good colorimeter should have.

Temporal, Spatial, and Environmental classification of Pine Reflectance Spectra.

To create consistent spectral data for evaluating geographical, chronological, and environmental differences or events in main Scots pine populations in Finland and Sweden, reflectance spectra from randomly sampled single pine individuals (N = 2069) were measured. The spectra were recorded in 1991-1993 during and after the growing season by using a mobile spectroradiometer working in the 390-1070 nm wavelength range. The spectral data was processed by using three independent statistical pattern recognition methods. Typical spectral shape differences between the growing seasons were observed due to the obvious phenological phase shift from year to year. This was verified by the observed differences inside the growing season. Longitudinal distinguishing characteristics of the pine spectra were greater than latitudinal ones. We are also able to classify pines growing in polluted and less polluted environments to the corresponding classes.

Manufacturing of freeform mirror by milling and altering its optical characteristics by Ns-laser polishing and ALD coatings

In this study we tested ns-laser and an atomic layer deposition (ALD) for polishing and coating CNC-machined aluminum freeform mirrors that are used in a compact multipoint fiber optical probe. Two types of ALD coatings, aluminum oxide and silicon dioxide were tested. The surface roughness of mirrors was analyzed prior to and after nanosecond-laser polishing and coating them on a Beneq TFS 200 ALD device. The freeform aluminum mirrors with and without coatings were then measured with optical profiler. The results show that improvement in the surface roughness can be seen with ns-laser polished and ALD coated aluminum surfaces.

Thermochromism in color measurement

Accurate color measurements have become more and more important during the past few decades. This is valid not only in physical research but also in industrial production, where the importance of accurate measurements is mainly due to increased quality requirements set by the customers of various goods. The development of technology enables more and more accurate measuring systems. While the accuracy has improved one has noticed, that many unexpected factors affect the color of an object. One of these factors is the temperature of the sample. It is known that for example the reflectance of the ceramic reference tiles used for calibration of colorimeters and spectrophotometers is temperature dependent. This phenomenon is called thermochromism, which is a reversible change of color of the sample as a function of temperature. It may be noticed already at room temperature if the temperature varies few centigrades. Red and orange samples are especially sensitive to temperature variation and may cause difficulties in precise color measurements. We show, how the phenomenon is based on physical processes and not only reflects the instability of red color pigments. We derive simple formulas, which are shown to explain the experimental data. We also discuss the meaning of thermochromism for color measurements, measure the magnitude of it and propose the experimental conditions to avoid this effect.

Natural Vision Data File Format as a New Spectral Image Format for Biological Applications

Many kinds of spectral image formats are used for various applications, but there is still no existing standard format. Natural Vision data file format is one of the best possible candidates for the standard of spectral image format due to its flexibility to adapt to various kinds of existing image format and capacity to include information needed for each application. In biology, the analysis of huge datasets acquired by various techniques requires the use of specific databases. In order to be able to combine different data, defining a standard spectral image format that includes biological parameters is of prime importance. This paper describes an attempt to use Natural Vision data file format for spectral images related to biology and highlights the merits of Natural Vision data file format as an application oriented spectral image format.