Space imaging systems are designed to gather information from vantage points not accessible on Earth. Some systems are designed to look back at the Earth to help us understand our planet better while others are designed to explore the vast universe around us. The diversity of applications between the space imaging systems ensures a new set of engineering challenges with each camera design. The cameras integrated into each space system are designed to meet specific image requirements, but the measure of image quality may be very different depending on the application. For example, Earth-imaging satellites designed for monitoring weather phenomena require high radiometric fidelity whereas Earth-imaging satellites designed for monitoring world events require high spatial resolution for clear visual interpretability. Image chain analysis is used to understand the image formation properties of novel designs and to better understand design trades. Image chain analysis has become an important image science tool for assessing and optimizing image quality in space imaging programs.

The analysis of the technologies for color films is followed by the comparisons in technology and performance between color films and digital still cameras. Since the image qualities of pictures taken by color films and digital still cameras are already good enough for amateur consumers, many people have come to use convenient digital still cameras. However, there are substantial differences in image quality and performance between them, which are based on the difference in technology, and provide the reason to predict that people will use color films in addition to digital still cameras in the future. Then, descriptions are made to indicate that various technologies cultivated in silver halide photography for many years are being extended to various new fields.

The field of medical imaging is undergoing a radical shift, from subjective interpretation to quantitative analysis and measurement. This transformation is well established in the clinical trials arena and is beginning to enter the diagnostic field as well. This article will consider the implications of this change in terms of instrumentation, procedure, and analysis. It will include a brief review of current imaging practices and standards, focusing primarily on the clinical trials arena, and will examine in detail the acquisition and analysis techniques that will be required to successfully complete the transition from qualitative to quantitative imaging.

A silver-free photothermal sensitive imaging system which captures a photo image with microcapsules and can be thermal processed has been investigated. The photosensitive functional compounds are encapsulated with the interface polymerization method. Scanning Electron Micrographs show that the shape and diameter of the resulting microcapsules are comparable with silver halide grains under the condition of a shear velocity at 7000 rpm and a protecting colloidal concentration of 4.5% polyvinyl alcohol. Microcapsules with size smaller than 1 μm have been synthesized, which can act as basic imaging cells with excellent resolution compared with silver halide materials. The infrared spectra indicate that the wall of the microcapsule is composed of polyurea. The thermal response of the wall material detected with the thermal gravimetric and differential scanning calorimetry technique show that the optimal thermal development temperature is about 135 °C. Image density research confirms that the mechanism of image formation may be ascribed to the penetrability variety of the microcapsule under given thermal condition after exposure.

The modulation transfer function (MTF) is a standard method used for estimating the image quality of a component for detail recording in an image forming system and for printing quality of the final products. This study focused on the measurement of MTF of nonprinted and printed silk fabrics and a correlation of the MTF data to sharpness of the printed silk fabric using the in-house formulated ink jet ink. The MTF of the surface was measured using the sinusoidal test pattern in contact with the fabric using spatial frequencies from 0.375 to 3.0 cycles/mm. The sinusoidal test target scanned by a microdensitometer in the reflection density mode. These data comprise two frequencies; the high frequency is the characteristic of the fabric while the low frequency is the light scattering of the yarns in contact with the sinusoidal target. The sinusoidal curves at the low frequency were used for further calculation of the MTF values. The result indicated that the measurement of MTF of silk fabric using the contact sinusoidal method can find the point spread function of silk fabrics. This research investigated the relationships of weave style and direction, wicking properties, and the MTF of four different silk fabrics with plain weave (silk A, C, and D) or twill weave (silk B). Dot gain by the Yule–Nielsen model was investigated. The coefficient d calculated by the MTF empirical model was 0.0604 and the coefficient n by the Yule–Nielsen model was 1.636 for silk D which had the lowest d and n coefficients compared with other silk fabrics, indicating good quality in terms of image sharpness.

Traditional vegetation indices are based on only a few spectral bands. However, hyperspectral spectrometers, such as the airborne visible infrared imaging spectrometer (AVIRIS), collect data with 224 contiguous spectral bands. Traditional vegetation index extraction methods lose much of the information contained in hyperspectral data. The universal pattern decomposition method (UPDM) is tailored for hyperspectral data analysis. In this article, we consider the UPDM as a type of multivariate analysis; standard patterns are interpreted as an oblique coordinate system and coefficients are thought of as the coordinates of a pixel's reflectance. This article describes UPDM hyperspectral data transformation of AVIRIS data, the performance of a vegetation index based on the universal pattern decomposition method (VIUPD), and the influences of a noise-to-vegetation index. The results demonstrate that the VIUPD is an effective vegetation information extraction approach for hyperspectral data. The VIUPD is more sensitive to vegetation conditions than the normalized difference vegetation index and enhanced vegetation index. Furthermore, noise influences can be neglected in<?xpp qj?> VIUPD computations, with satisfactory accuracy.

In numerous prior works, a technique called Artificial Color has been developed to extract pixels belonging to a prespecified class while rejecting pixels belonging to other prespecified sets with great reliability. The heart of the algorithm is another well described pattern recognition method called Margin Setting. Margin Setting achieves highly reliable classification by refusing to classify some borderline pixels. As a result, the image produced using Artificial Color methods is reliable in finding the target of interest but that target may contain unclassified pixels, leading to a spotty or ragged image being extracted. It is showed here that post processing that ragged image using mathematical morphology can improve the extracted image substantially, and median filtering after that produces even more improvement.

In this article, we present a fast switching filter for impulsive noise removal from color images. The filter exploits the hue, saturation, and lightness color space and is based on the peer group concept, which allows for the fast detection of noise in a neighborhood without resorting to pairwise distance computations between each pixel. Experiments on large set of diverse images demonstrate that the proposed approach is not only extremely fast, but also gives excellent results in comparison to various state-of-the-art filters.

The sensor response of a camera can be represented as the stimulus multiplied by the spectral distribution of an ambient illuminant, the surface reflectance of an object, and camera sensitivity. Surface reflectance is one of the most significant factors that indicates an object's color; therefore its estimation has received widespread attention. Among conventional methods for estimating surface reflectance, principal component analysis (PCA) has an advantage because it uses only one set of principal components for an entire reflectance population. There are limitations, however, in estimating all reflectance using this PCA method with only one set of principal components. In this article, an algorithm is proposed to estimate surface reflectance by using principal components determined by subgroups with similar colors, which are classified from the entire reflectance population. In order to compose a subgroup with similar colors, the Macbeth ColorChecker is utilized to obtain initial representative surface reflectance values for an entire reflectance population; then the Munsell chips are divided into subgroups with different principal components. Moreover, initial representatives have to be modified to avoid biased representations for the population because the Macbeth ColorChecker does not provide optimal representations for the entire reflectance population, even though it is evenly spaced in the CIELAB color space. Therefore, the mean value of each subgroup is used to obtain new representatives, and the new subgroups of reflectance are composed by using the Lloyd quantizer design algorithm. Then, the PCA method is applied for the principal components of the subgroup including surface reflectance. To evaluate its performance, the proposed estimation method was compared with that of a conventional three-band principle component analysis. The proposed method provided better results in its performance.

Inverse characterization in a printing device is the process to find control values of colorants to print out any input stimulus values (CIEXYZ, CIELAB, etc.). In a CMY-type printer, the control values can be simply estimated through the interpolation process using a lookup table with a one-to-one relation between the control values and the stimulus values. In a multicolorant printer with extra colorants like red (orange), blue, and green, however, since it has one to many correspondences between CIELAB values and control values, an appropriate control value must be selected from many candidate control values which have negligible color differences from input stimulus value. Selecting a control value without any restriction tends to induce interpolation errors because it does not consider the relation between neighbor control values. In this article, we propose an improved inverse characterization method for multicolorant printer to reduce interpolation errors using the correlation between distributions of control values. We first sampled the CIELAB values regularly in CIELAB space in order to find the appropriate control values for each CIELAB value, since a color stimulus can be represented by several control values of colorants in a multicolorant printer. To find control values for the sampled CIELAB values, the colorant space is sampled and the CIELAB values for all combinations of control values were estimated using the Cellular Yule Nielsen Neugebauer spectral model. The control value whose estimated CIELAB value was close to a sampled CIELAB value was extracted as a candidate for the appropriate control value of the sampled CIELAB value. Subsequently, the most appropriate candidate was selected by considering global and local correlation. For this purpose, we selected all control values for the sampled CIELAB values so that all the selected control values had higher similarity than the predefined threshold in the distribution of colorant amount for global selection step. In addition, in the local selection step, regarding the sampled CIELAB values for which we could not select a control value via this global selection step, the control value was reselected by comparing similarities between the neighbor selected control values and candidates in CIELAB space. Then, accurate CIELAB values of the selected control values were measured and stored in the lookup table. To evaluate the proposed inverse characterization method, a CMYKGO printer was utilized. The proposed method effectively reduced the color difference in the interpolation process. Moreover, the gamut was extended partially and the continuous tone could be represented more smoothly than by conventional methods.