This paper presents a new technique for embedding information inside a 3-D printed object. The information is added to the 3-D model data, and when the 3-D printed object is fabricated using the data, the dispositions of fine domains, which express the information, are simultaneously formed inside. In this study, fine cavities are formed as fine domains, and the thermal conductivity of the cavity is lower than the main body of the object filled with the material. Therefore, the disposition of the cavities can be detected from the surface temperature of the object. Experiments were conducted using a fused deposition-modeling 3-D printer and thermography, and their results revealed cavities as small as 2 × 2 mm in size could be detected even when the surface was curved. We demonstrated the proposed technique was feasible.

Sensor interpixel correlation (IC), as caused by crosstalk, interpixel capacitance, the brighter–fatter effect, blooming or smear, lowers the sensor MTF and increases color distortion in color filter array sensors. This is generally overlooked, and challenging to mitigate. Recent findings regarding scientific grade (CCD or hybrid CMOS) sensors, describe non-linearities causing pixel charge accumulation dependent IC. This is relevant even for lower grade sensors. High dynamic range imaging (HDRI) is especially susceptible to IC, because the sensor is deliberately operated partly in saturation. Existing HDRI algorithms exclude saturated pixels but generally overlook IC. This review article motivates the need for a generalization of the point spread function (PSF) into an irradiance-exposure dependent (IED) PSF, also considering supersaturation. The IED PSF is challenging to characterize and apply, partly due to its non-linearity. However, doing so can improve the MTF irrespective of image sensor technology, and for conventional as well as HDRI imaging.

Single source images do not contain the comprehensive information of the target and the target recognition rate is low. Targeting to these problems, a new target recognition method based on fusing features of the target in Visible (VIS), Middle Wave Infrared (MWIR) and Long Wave Infrared (LWIR) images is proposed. First, typical features of the target in VIS, MWIR and LWIR images are extracted. The fused feature vector is subsequently obtained by feature selection based on Fisher discriminant analysis. Finally, target recognition is realized through Support Vector Machine (SVM). The target recognition performance of the proposed method and five other target recognition algorithms were tested and compared on VIS, MWIR and LWIR images. Experimental results illustrate that the target recognition rate of the proposed algorithm is higher than that of the five other algorithms tested. The proposed algorithm also has high operational efficiency and robustness.

In this paper, a method for adaptive pure interpolation (PI) in the frequency domain, with gradient auto-regularization, is proposed. The input image is transformed into the frequency domain and convolved with the Fourier transform (FT) of a 2D sampling array (interpolation kernel) of initial size L rows by M columns. The inverse Fourier transform (IFT) is applied to the output coefficients and the edges are detected and counted. To get a denser kernel, the sampling array is interpolated in the frequency domain and convolved again with the transform coefficients of the original image of low resolution and transformed back into the spatial domain. The process is repeated until a maximum number of edges is reached in the output image, indicating that a locally optimal magnification factor has been attained. In a next step a maximum ascend–descend gradient auto-regularization method is designed and the edges are sharpened. For the gradient management, a new strategy is proposed, referred to as the natural bi-directional gradient field (NBGF). It uses a natural following of a pair of directional and orthogonal gradient fields. Finally we find a novel procedure based on the observation of auto-regularized gradient management (ARG) in which a direct and compact mathematical proposition is applied effectively. A development of series of derivatives constructs directly the gradient field without parameters of experimental initialization. The proposed procedure is comparable to novel algorithms reported in the state of the art with good results for high scales of amplification.

Non-rigid image registration is an important preprocessing step in many medical image applications, but it is also a very computation intensive task. In this paper, a fast adaptive bases (FAB) non-rigid image registration with local optimization method is proposed to speed up the free-form deformation with radial basis functions. Our proposed algorithm applies matched area identification in the initialization process and adaptive support size for basis function in the misregistration region identification process. Moreover, higher grid point density for local optimization is used in the identified misregistration regions. With our proposed algorithm, the registration speed is found significantly increased while maintaining the registration accuracy. The overall running time is reduced by preserving the advantage of computing local deformation on disjoint regions instead of trying to solve the problem globally. Performance evaluation of our proposed method was conducted using simulated and clinical brain dataset with standard measures based on root mean square error (RMSE) and normalized mutual information (NMI) similarity measure. Experimental results showed that notable improvement on speed was achieved as compared to the conventional regular and adaptive grid approaches.

The projection on screen has always been the supreme result of cinematography. Thus the digitization of a motion picture should seek to recreate the visual impression in the cinema. The image-forming particles contained in early color films can generate remarkable differences between a film directly observed with diffuse backlighting and its image projected on screen. In the recent decades this discrepancy has been largely overlooked by the film preservation community (film curators, scanner manufacturers, colorists, etc.). This paper re-establishes the importance of referring to the visual impression in the cinema, and describes the spectral variation of the Callier effect that can significantly alter early film colors when digitized. We have introduced the term “chromatic Callier effect” and described its repercussions on film digitization reporting case studies of tinted and toned film prints. The experimental results highlight that important changes are required in the optical design of film scanners to improve the digitization of motion pictures.

In this paper, we analyze the relationship between impression of facial skin and skin component distribution by applying canonical coefficient analysis (CCA) to multiple physical and psychological features obtained from facial images. Based on the acquired relationship, we modulate the skin pigment features, and appearances of the face with arbitrary psychological features are reproduced. In our previous work, we applied principal component analysis (PCA) to the melanin pigment variation of the facial skin, and we obtained individual differences in it occurring over 7 years. In the previous method, as the factor causing individual difference, we considered the frequency of UV protection. However, actual skin appearance is thought to depend not only on melanin but also on several other factors. Therefore, in this study, we captured facial images of females aged from 10s to 80s at intervals of 12 years, and we obtained not only physical but also psychological features. As physical features, melanin and hemoglobin pigment and shading distributions, and the frequency of UV protection for 12 years were obtained. Psychological feature values were acquired as subjective evaluation. As a result of CCA on the physical features only, it was found that the whole face can be made lighter in appearance by performing UV protection every day continuously for 6 years or more. As a result on both physical and psychological features, pigment features greatly affecting the impression of the skin and multiple skin aging patterns were obtained. According to this result, the pigment features were modulated, and facial appearances with arbitrary psychological features were reproduced.