An image emotion space defining the relationship between the manipulation of a photographic image and the resulting change in the impression it produces was constructed by presenting original images and their manipulated versions in pairs to a panel of ob- servers and asking them to identify the one giving the stronger impression for each of 59 emotion words. Picture-independent results could be obtained by comparing raw images of various pictures with those having various effects applied at random. Components governing the responses were extracted from the results by principal component analysis to construct a two-dimensional space with the components lightness and contrast and chroma as axes. Furthermore, it was shown that the differences in impressions can be clustered into 12 clusters by cluster analysis. A Kansei space model showing pathways to “preferred” was obtained by multiple linear regression analysis using “preferred” as the dependent variable and the representative words of their respective clusters as the inde- pendent variable. It consisted of two pathways, one for lightness information and one for color information.

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We propose a method that uses the point spread function of specular reflection (SR-PSF) to simulate paper gloss. The SR-PSF is defined as the impulse response of specular reflection, which is the distribution of light intensity reflected from microscopic facets on the surface of the paper. In this study, we used a flat sample holder and measured the SR-PSFs of six paper samples, each of which had a different level of specular gloss. We then used two different methods based on the measured SR-PSFs to simulate the gloss of curved paper. The results show that the gloss of curved paper can be adequately simulated by using the measured SR-PSF of that pa- per.

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It was revealed that estimated vegetation indices with a commercial digital camera have shown anomalously high values over 0.9 in NDVI (Normalized Difference Vegetation Index) for a shady area of the camera images. It was manifested that an exclusion of pix- els of the camera image with luminance below a threshold is a key method to remove the shady area and to acquire much better esti- mation of vegetation index. Appropriate luminance for the purpose requires us to exclude pixels of the image with luminance below about 70 out of 255. Successful removal of shady/anomalous NDVI areas and excellent estimation of vegetation index from the im- ages of the specific digital camera were obtained.

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Au nano-rod array membrane was prepared using a commercially-available porous anodic aluminum oxide plate as the template which consisted of branched structures. When a NiO film was immobilized on the nano-rod surface of the obtained membrane, the electrochromic response of the NiO film was remarkably accelerated: the total process including the coloring and bleaching was ac- celerated 1.2 times, in particular, the bleaching process was significantly accelerated 1.5 times.

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